Objective: To evaluate the clinical efficacy of digitally guided precision crown lengthening in secondary aesthetic rehabilitation cases, and to provide a clinical reference for digitally guided crown lengthening procedures and secondary aesthetic restorations. Methods: We present a case of a patient with tetracycline-stained teeth, partial detachment of anterior resin veneers, and gingival margin discrepancies. The patient underwent digitally guided precision crown lengthening followed by secondary aesthetic rehabilitation. Multimodal data, including intraoral, facial, and CBCT scans, were integrated to construct a four-dimensional virtual patient model (incorporating teeth, face, bone, and occlusion) for surgical planning and 3D-printed guide fabrication. Secondary aesthetic restoration was performed after achieving stable post-surgical outcomes. Based on this case, we conducted a detailed analysis and reviewed relevant literature on crown lengthening in secondary aesthetic rehabilitation. Results: The gingival contour of the anterior teeth exhibited significant improvement, with enhanced symmetry and stable gingival margin positioning that closely matched the preoperative design. The crown lengthening procedure demonstrated high precision, and the final outcome was aesthetic and functional. Literature review indicated that secondary restorations frequently present challenges such as gingival contour discrepancies and inflammation. Aesthetic crown lengthening in the anterior region should optimize both soft and hard tissue morphology to meet aesthetic standards, with digital technology improving procedural accuracy. Conclusion Precision crown lengthening effectively addresses gingival margin discrepancies in secondary aesthetic rehabilitation, ensuring stable gingival positioning and superior aesthetic outcomes. This approach is particularly suitable for cases with high aesthetic demands.

Objective To explore the changes and influencing factors in patients' gastrointestinal symptoms and food tolerance before and after laparoscopic sleeve gastrectomy(LSG),and to provide a reference for the development of targeted gastrointestinal symptoms management program.Methods A convenience sampling method was used to select 125 patients who underwent LSG in the bariatric and metabolic surgery department of a tertiary-level hospital in Xuzhou City from June to November 2023 for a prospective observational study.The general information questionnaire,food tolerance questionnaire and Gastrointestinal Symptom Rating Scale(GSRS)were used to investigate at preoperative,3 months after surgery,and 6 months after surgery.Two-factor repeated measures variance analysis and generalized linear mixed model(GLMM)was used to analyze the influencing factors of gastrointestinal symptoms.Results 116 valid questionnaires were collected,and the GSRS scores of LSG patients at 3 time points were 21.67±5.80,23.28±4.33,and 21.22±3.18 respectively;the incidence rates of food intolerance were 0,32.75％,and 28.45％respectively.The patients' symptoms of bowel sounds,dysphagia,constipation,and dry stool were worse after surgery than before surgery(all P＜0.05),and the symptoms of bad breath,diarrhea,loose stools,and the need to defecate immediately were alleviated compared with symptoms before surgery(all P＜0.05).GLMM results showed that short meal times,poor food tolerance,and high school/technical secondary school education were risk factors for increasing gastrointestinal symptoms(all P＜0.05).Conclusion LSG could increase the prevalence of gastrointestinal symptoms such as dysphagia,dyspepsia,constipation and food intolerance.Medical staff should pay attention to the assessment of gastrointestinal symptoms in LSG patients,especially for patients with short meal time and poor food tolerance,strengthen postoperative follow-up,build targeted treatment and care plan,and prevent and reduce such uncomfortable symptoms.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective To explore the changes and influencing factors in patients' gastrointestinal symptoms and food tolerance before and after laparoscopic sleeve gastrectomy(LSG),and to provide a reference for the development of targeted gastrointestinal symptoms management program.Methods A convenience sampling method was used to select 125 patients who underwent LSG in the bariatric and metabolic surgery department of a tertiary-level hospital in Xuzhou City from June to November 2023 for a prospective observational study.The general information questionnaire,food tolerance questionnaire and Gastrointestinal Symptom Rating Scale(GSRS)were used to investigate at preoperative,3 months after surgery,and 6 months after surgery.Two-factor repeated measures variance analysis and generalized linear mixed model(GLMM)was used to analyze the influencing factors of gastrointestinal symptoms.Results 116 valid questionnaires were collected,and the GSRS scores of LSG patients at 3 time points were 21.67±5.80,23.28±4.33,and 21.22±3.18 respectively;the incidence rates of food intolerance were 0,32.75％,and 28.45％respectively.The patients' symptoms of bowel sounds,dysphagia,constipation,and dry stool were worse after surgery than before surgery(all P＜0.05),and the symptoms of bad breath,diarrhea,loose stools,and the need to defecate immediately were alleviated compared with symptoms before surgery(all P＜0.05).GLMM results showed that short meal times,poor food tolerance,and high school/technical secondary school education were risk factors for increasing gastrointestinal symptoms(all P＜0.05).Conclusion LSG could increase the prevalence of gastrointestinal symptoms such as dysphagia,dyspepsia,constipation and food intolerance.Medical staff should pay attention to the assessment of gastrointestinal symptoms in LSG patients,especially for patients with short meal time and poor food tolerance,strengthen postoperative follow-up,build targeted treatment and care plan,and prevent and reduce such uncomfortable symptoms.

In recent years, the prevalence of gestational diabetes mellitus (GDM) has significantly increased, leading to various adverse outcomes for mothers and their offspring. Early diagnosis and good blood glucose control can significantly improve pregnancy outcomes. Currently, the diagnosis of GDM mainly relies on the oral glucose tolerance test (OGTT), but there are many limitations in clinical application. The new biological marker glycosylated CD59 is a glycosylation product of complement regulatory proteins that can stably exist in body fluids and is linearly related to blood glucose levels, which has the advantages of simple testing and good reproducibility, and has been developed into a stable reagent kit. It has shown good value in the early diagnosis, standard diagnosis, and prediction of pregnancy outcomes of GDM.

Objective To investigate the impact of the Shared Medical Appointment (SMA) model on blood glucose levels and self-management behaviors in patients with gestational diabetes mellitus (GDM). Methods A total of 87 pregnant women diagnosed with GDM at the Obstetrics and Gynecology and Endocrinology Outpatient Departments of the Affiliated Suqian Hospital of Xuzhou Medical University from October 2021 to October 2022 were enrolled and divided into treatment group (n=44) and control group (n=43). The treatment group received SMA-based GDM management, while the control group underwent routine outpatient follow-up. Baseline data, flash glucose monitoring (FGM)-related indicators before and after treatment, and self-management behavior scale scores were compared between the two groups. Results No statistically significant differences were observed between the two groups in age, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), blood urea nitrogen (BUN), creatinine (Cr), uric acid (UA), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glycated hemoglobin (HbA1c) (P>0.05). After treatment, the time in range (TIR) of glucose was higher in the treatment group than that in the control group, while mean amplitude of glycemic excursions (MAGE), standard deviation of blood glucose (SDBG), coefficient of variation (CV), and mean blood glucose (MBG) were lower in the treatment group (P < 0.05). Within the treatment group, post-treatment TIR was higher, and MAGE, CV, SDBG, and MBG were lower than pre-treatment levels (P < 0.05). In the control group, post-treatment TIR was higher, and SDBG and MBG were lower than pre-treatment levels (P < 0.05). After treatment, the total score and scores for dietary management, exercise management, medication management, and blood glucose monitoring management in the self-management behavior scale were significantly higher in the treatment group than in the control group (P < 0.05). In the treatment group, post-treatment scores for all self-management behaviors were higher than pre-treatment levels, while post-treatment total scores and scores for medication management and blood glucose monitoring management in the control group were higher than pre-treatment levels (P < 0.05). Conclusion SMA management model can comprehensively improve blood glucose levels and enhance self-management behavior capabilities in GDM patients.

Tryptophan metabolism plays an important role in immunometabolism in sepsis,and the expression of indoleamine 2,3-dioxygenase 1(IDO1),the key enzyme of tryptophan metabolism,is up-regulated during sepsis.This study was designed to construct IDO1 gene knockout THP-1 cell line using CRISPR/Cas9,and to provide a cell model for studying the role of IDO1 in macrophage function.Three gRNAs were designed for the IDO1 gene,and inserted into YKO-Lentiviral gRNA plasmid respectively to construct IDO1-gRNA recombinant plasmid,which then confirmed by restriction enzyme digestion and sequencing,and packaged as Lenti-IDO1-gRNA lentivirus.THP-1 cells were infected with Cas9 lentivirus to construct a THP-1 Cas9 cell line stably expressing Cas9 protein.Then THP-1 Cas9 cells were infected with the Lenti-IDO1-gRNA lentivirus for IDO1 gene knockout,and the monoclonal cell lines were screened by limited dilution method.The efficiency of IDO1 knockout was identified by T7E1 digestion test,PCR product sequencing and Western blotting.The proliferative activity of THP-1 cells was detected by CCK8 assay;the expression of CD11b,CD68 and CD 14 in THP-1 macrophages were detected by flow cytometry;and the phagocytic function of THP-1 macrophages was detected by neutral phagocytosis test.T7E1 restriction enzyme digestion results showed that all the three gRNAs could effectively edit IDO1 gene,and gRNA2 had the highest editing efficiency.Sequencing of PCR products showed that IDO1 gene was mutated in three THP-1 IDO 1-KO monoclonal cell lines,and Western blot result showed that IDO1 protein was not expressed,suggesting THP-1 IDO1-KO cells were successfully constructed.CCK-8 proliferation assay showed that IDO1 gene knockout could inhibit the proliferation of THP-1 cells.Flow cytometry showed that IDO1 gene knockout down-regulated the expression of CD1 1b and CD68 in THP-1 macrophages,while up-regulated the expression of CD 14.The results of neutral red phagocytosis test showed that IDO1 gene knockout promoted the phagocytosis of macrophages.In conclusion,the IDO1 gene knockout THP-1 cell line has successfully constructed by CRISPR-Cas9,and IDO1 plays an important role in regulating the proliferation activity and differentiation of THP-1 cells,as well as the phagocytic function of THP-1 macrophages.

Objective:To understand the infection status and molecular types of rhinovirus (RV) among cases of Acute Respiratory Infections (ARIs) in Luohe City, Henan Province, from 2017 to 2022.Methods:From October 2017 to June 2022, clinical and epidemiological data were collected from 2 270 cases of ARIs at Luohe Central Hospital in Henan Province. Throat swab specimens were obtained from these cases. Real-time quantitative polymerase chain reaction (qPCR) was used to screen for RV-positive specimens. Subsequently, the positive samples were subjected to nested reverse transcription polymerase chain reaction (nested RT-PCR) to amplify the full-length VP1 region. Using the MEGA software, along with 169 RV reference strains recommended by the International Committee on Taxonomy of Viruses, a phylogenetic tree was constructed to determine RV types.Results:Among the 2 270 cases of ARIs, there were 1 283 male cases (56.52%). The median age ( Q 1, Q 3) was 3 (1, 6) years, with the population under 5 years old accounting for 68.59% (1 557/2 270). RV was detected in 137 cases (6.04%), of which 68 cases (49.64%) showed co-detection with other viruses, with the most common being co-detection with enterovirus, accounting for 14.60% (20/137). The RV detection rates in the age groups of 0-4 years, 5-14 years, 15-59 years, and≥60 years were 6.42% (100/1 557), 4.69% (21/448), 3.80% (6/158), and 9.35% (10/107), respectively, with no statistically significant differences ( χ2=5.310, P=0.150). The overall detection rates of RV before (2017-2019) and during (2020-2022) the COVID-19 pandemic showed no statistically significant difference ( χ2=1.823, P=0.177). A total of 109 VP1 sequences were obtained, including 62 types. Among them, RV-A, RV-B, and RV-C had 42, 3, and 17 types respectively. Conclusion:RV is one of the predominant pathogens in ARIs cases in Luohe City, Henan Province, from 2017 to 2022. Multiple types of RV co-circulate without any apparent dominant type.