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.

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 investigate effectiveness of arthroscopic superior capsular reconstruction using a "sandwich" patch combined with platelet-rich plasma (PRP) injection in treating massive irreparable rotator cuff tears. METHODS: A clinical data of 15 patients (15 sides) with massive irreparable rotator cuff tears, who were admitted between September 2020 and March 2023 and met the selective criteria, was retrospectively analyzed. There were 8 males and 7 females with an average age of 62.1 years (range, 40-80 years). The rotator cuff tears were caused by trauma in 7 cases and other reasons in 8 cases. The disease duration ranged from 5 to 25 months, with an average of 17.7 months. According to the Hamada grading, the rotator cuff tears were rated as grade 1 in 2 cases, grade 2 in 8 cases, and grade 3 in 5 cases. All patients were underwent superior capsular reconstruction using the "sandwich" patches (autologous fascia lata+polypropylene patch+autologous fascia lata) combined with PRP injection on patches. The pre- and post-operative active range of motion (ROM) of the shoulder joint, American Shoulder and Elbow Surgeons (ASES) score, Constant-Murley score, University of California, Los Angeles Shoulder Rating Scale (UCLA) score, and visual analogue scale (VAS) score were recorded. The subacromial space was measured on the imaging and rotator cuff integrity was assessed based on Sugaya grading. RESULTS: All incisions healed by first intention after operation without any complications such as infection. All patients were followed up 12-18 months (mean, 14.4 months). At last follow-up, the active ROMs of flexion, abduction, external rotation, internal rotation of the shoulder joint, subacromial space, ASES score, Constant-Murley score, and UCLA score increased, and VAS score decreased, showing significant differences when compared with preoperative values ( P<0.05). There was no significant difference in the Sugaya grading between last follow-up and immediately after operation ( P>0.05). CONCLUSION For massive irreparable rotator cuff tears, arthroscopic superior capsular reconstruction using the "sandwich" patches combined with PRP injection can restore stability of the shoulder joint, relieve pain, promote rotator cuff healing, and achieve good short-term effectiveness.
Humans ; Platelet-Rich Plasma ; Female ; Male ; Middle Aged ; Aged ; Rotator Cuff Injuries/therapy* ; Arthroscopy/methods* ; Adult ; Retrospective Studies ; Aged, 80 and over ; Treatment Outcome ; Plastic Surgery Procedures/methods* ; Rotator Cuff/surgery* ; Range of Motion, Articular ; Shoulder Joint/surgery*

OBJECTIVE: To establish and validate a novel diabetic retinopathy (DR) risk-prediction model using a whole-exome sequencing (WES)-based machine learning (ML) method. METHODS: WES was performed to identify potential single nucleotide polymorphism (SNP) or mutation sites in a DR pedigree comprising 10 members. A prediction model was established and validated in a cohort of 420 type 2 diabetic patients based on both genetic and demographic features. The contribution of each feature was assessed using Shapley Additive explanation analysis. The efficacies of the models with and without SNP were compared. RESULTS: WES revealed that seven SNPs/mutations ( rs116911833 in TRIM7, 1997T>C in LRBA, 1643T>C in PRMT10, rs117858678 in C9orf152, rs201922794 in CLDN25, rs146694895 in SH3GLB2, and rs201407189 in FANCC) were associated with DR. Notably, the model including rs146694895 and rs201407189 achieved better performance in predicting DR (accuracy: 80.2%; sensitivity: 83.3%; specificity: 76.7%; area under the receiver operating characteristic curve [AUC]: 80.0%) than the model without these SNPs (accuracy: 79.4%; sensitivity: 80.3%; specificity: 78.3%; AUC: 79.3%). CONCLUSION Novel SNP sites associated with DR were identified in the DR pedigree. Inclusion of rs146694895 and rs201407189 significantly enhanced the performance of the ML-based DR prediction model.
Diabetic Retinopathy/diagnosis* ; Humans ; Machine Learning ; Male ; Female ; Polymorphism, Single Nucleotide ; Middle Aged ; Exome Sequencing ; Aged ; Adult ; Pedigree ; Diabetes Mellitus, Type 2/complications* ; Genetic Predisposition to Disease ; Mutation

The traditional commodity specifications of Chinese medicinal materials are mainly divided into different grades based on macroscopic characteristics. As the basis for high quality and good price, there is still a lack of systematic evaluation on whether they are consistent with the current standards and whether they can reflect the internal quality of medicinal material. Panax notoginseng is a commonly used, large consumption of Chinese medicinal material. At present, it is divided into 8 grades in the market based on "Tou" (the number of crude drug /500 g), but it is not related to the standard of total saponins of Panax notoginseng (the sum of three saponins) in Chinese Pharmacopoeia. In this study, ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS/MS) coupled with mass spectrometry molecular network were used for the rapid identification of saponins of Panax notoginseng with different "Tou" and a total of 64 saponins were identified. Seventeen saponins related to "Tou" were screened by orthogonal partial least squares discriminant analysis (OPLS-DA). The content of five saponins R₁, Rb₁, Rg₁, Rd, and Re in Panax notoginseng with different "Tou" was determined by high performance liquid chromatography (HPLC). The results of correlation analysis showed that Rd and R₁ with the largest VIP values among the differential saponins, which significantly negatively correlated with "Tou" (P < 0.05). Based on the determination results of 36 batches of samples, using Rd/Total Panax notoginseng saponins (TPNS) ratio ( > 0.08) as the index, Panax notoginseng can be divided into two grades: 20-60 "Tou" (superior) and 80-200 "Tou" (qualified). Based on the concept of "macroscopic characteristics and chemical profiling", this study integrates the non-targeted analysis and quantitative determination methods to provide a new strategy for quality evaluation of Panax notoginseng.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

The UV cross-linking immunoprecipitation (CLIP) technique was first established in 2003. Sequences of target RNAs and binding sites of specific RNA-binding proteins (RBPs) were identified within the entire transcriptome by UV cross-linking, immunoprecipitation, reverse transcription, and subsequent high-throughput sequencing. Over the last 20 years, CLIP has been continuously modified and improved. Advanced operability and accuracy have extended its application category. Currently, the widely used CLIP technologies include high-throughput sequencing with crosslinking-immunoprecipitation (HITS-CLIP), photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP), individual nucleotide resolution CLIP (iCLIP), enhanced CLIP (eCLIP), infrared-CLIP (irCLIP), etc. HITS-CLIP combines high-throughput sequencing with UV cross-linking immunoprecipitation. The 254 nm UV cross-linking and RNAase digestion steps allow the technology to capture transient intracellular RBP-RNA interactions. However, there are limitations in the efficiency of UV cross-linking, with low resolution and high intrinsic background noise. For PAR-CLIP, photoactivatable ribonucleoside was incorporated into RNA molecules, and RBP cross-linked with RNA by 365 nm UV light to improve cross-linking efficiency and resolution. Cross-linking mediated single-base mutations provide more accurate binding site information and reduce interference from background sequences. Long-term alternative nucleotide incorporation, on the other hand, can be cytotoxic and may skew experimental results. iCLIP can identify RBP-RNA cross-linking sites at the single nucleotide level through cDNA circularization and subsequent re-linearization steps, but it has more experimental procedures, and partial cDNAs lost in the circularization step are inevitable. eCLIP discards the radioisotope labeling procedure and reduces RNA loss by ligating adaptors in two separate steps, greatly improving the library-building efficiency, and reducing bias associated with PCR amplification; however, the efficiency of immunoprecipitation cannot be visually assessed at the early stage of the experiment. The irCLIP technique replaces radioisotopes with infrared dyes and greatly reduces the initial number of cells required for the experiment; however, an infrared imaging scanner is essential for the irCLIP application. To address more particular scientific issues, derivative CLIP-related techniques such as PAPERCLIP, cTag-PAPERCLIP, hiCLIP, and tiCLIP have also been developed in recent years. In practice, the aforementioned CLIP approaches have their advantages and disadvantages. When deciding on a technical strategy, we should take into account our experimental objectives and conditions, such as whether we need to precisely define the RNA site for binding to RBP; whether we have the necessary experimental conditions for working with radioisotopes or performing infrared imaging; the amount of initial sample size, and so on. In addition, the CLIP technique has a relatively large number of procedures and can be divided into several successive experimental modules. We can try to combine modules from different mainstream CLIP technologies to meet our experimental requirements, which also gives us more opportunities to improve and refine them and to build more targeted derivative CLIP technologies according to our research objectives.