OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE To study the pharmacokinetic characteristics of antidepressant active components from Jiaotai pills in healthy subjects. METHODS Eight healthy subjects （3 males and 5 females） were recruited and given a single oral dose of 8.55 g of Jiaotai pills. Venous blood samples were collected before administration （0 h） and at intervals from 0.25 to 36.0 hours post- administration. After treating the plasma samples with protein precipitation， the blood concentrations of the antidepressant active ingredients （coptisine， berberine， magnoflorine， and palmatine） in Jiaotai pills were determined using liquid chromatography- tandem mass spectrometry （LC-MS/MS） method. DAS 2.0 software was employed to calculate the pharmacokinetic parameters of healthy subjects [half-life （t1/2）， peak concentration （cmax）， time to peak concentration （tmax）， area under the concentration-time curve （AUC）， and mean residence time （MRT）] using a non-compartmental model. RESULTS After healthy subjects took Jiaotai pills， the drug-time curve of the four antidepressant active ingredients conforms to a two-compartment model and tmax values were similar， with all reaching peak blood concentrations within 2.00 to 4.00 hours post-administration. However， the t1/2 and MRT of coptisine and berberine were significantly longer than that of magnoflorine and palmatine. There were also significant differences in the AUC and cmax among the four antidepressant active ingredients， with magnoflorine exhibiting markedly higher AUC0-t and cmax compared to the other three components. CONCLUSIONS In this study，LC-MS/MS is used to analyze the pharmacokinetic characteristics of the antidepressant active ingredients from Jiaotai pills in healthy subjects， can provide valuable references for the clinical application of Jiaotai pills.

Objective To investigate the causes and management strategies for lower limb ischemic necrosis following xenogeneic heterotopic heart transplantation from a multigene-edited pig to a rhesus monkey. Methods A xenogeneic heterotopic heart transplantation was performed on December 16, 2023, at the Institute of Experimental Animals of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, using a quintuple-gene-edited pig as the donor and a rhesus monkey as the recipient. On postoperative day (POD) 9, the recipient monkey underwent left lower limb amputation due to ischemic necrosis. Blood samples were collected at various time points after transplantation for analysis of hematologic parameters, liver and renal function, myocardial enzymes, and coagulation profiles. Ultrasound and computed tomography (CT) were used to evaluate anastomotic patency and cardiac structure. Immunological assays, including complement-dependent cytotoxicity (CDC) and IgG/IgM antibody detection, combined with clinical observations, were employed to assess rejection type and therapeutic response. Results The recipient monkey survived for 46 days after transplantation. Echocardiography demonstrated preserved biventricular systolic function in the recipient’s native heart, with left ventricular ejection fraction (LVEF) consistently exceeding 50%. In the donor pig heart, left ventricular endocardial thickening was noted on POD 9, followed by right ventricular endocardial thickening on POD 24, while LVEF remained around 35%. No hyperacute or acute rejection was detected immunologically. CDC positivity ranged between 3.4% and 5.1%, with IgG/IgM antibody binding trends consistent with CDC results. Following amputation, the recipient exhibited elevated inflammatory markers, coagulopathy, and reactive thrombocytosis, which later normalized. Immunohistochemical staining of the necrotic limb revealed arterial and venous thrombosis; however, no T-cell or B-cell infiltration was observed in vascular structures, thrombi, nerves, muscles, fascia, or skin tissues, with CD3 and CD20 staining both negative. Conclusion Limb ischemia after xenogeneic heart transplantation may be associated with lower extremity vascular thrombosis triggered by local trauma in the context of transplantation-induced inflammatory activation and coagulation dysfunction. While no clear lymphocyte-mediated rejection was observed, further studies are needed to explore the potential role of non-lymphocyte-mediated immune mechanisms.

ObjectiveTo investigate the neuroprotective effect of glycosides of cistanches （GCs） in 1-methyl-4-phenyl-1，2，3，6-tetrahydropyridine （MPTP）-induced Parkinson’s disease （PD） model mice and its potential mechanism. MethodsForty mice were randomly divided into control group， PD group， GCs group and levodopa （L-DOPA） group， with 10 mice in each group. The control group received intraperitoneal injection of normal saline， while the other groups were intraperitoneally injected with MPTP （30 mg/kg） once daily for 5 consecutive days. After model establishment， the control group and PD group were intragastrically administered normal saline， and the GCs group and L-DOPA group received intragastric administration once daily for 28 consecutive days， at doses of 100 mg/kg and 50 mg/kg， respectively. The open field test and rotarod test were used to evaluate motor function. Immunohistochemistry was performed to detect the number of tyrosine hydroxylase （TH）-positive neurons in the substantia nigra of the midbrain. Transmission electron microscopy was adopted to observe the ultrastructure of mitochondria in the substantia nigra. Biochemical assays were used to determine the levels of glutathione （GSH）， malondialdehyde （MDA）， total superoxide dismutase （T-SOD） and reactive oxygen species （ROS） in substantia nigra tissues. Western blot was applied to detect the protein expression of TH， nuclear factor erythroid 2-related factor 2 （Nrf2）， Kelch-like ECH-associated protein 1 （Keap-1） and heme oxygenase-1 （HO-1） in substantia nigra tissues. ResultsCompared with the control group， mice in the PD group exhibited markedly impaired motor function， significantly decreased T-SOD activity， obvious reductions in the number of TH-positive neurons and GSH content， as well as elevated MDA and ROS levels in the substantia nigra （P<0.01）. Compared with the PD group， mice in the GCs group showed improved motor function， increased T-SOD activity， higher number of TH-positive neurons and elevated GSH content， accompanied by decreased MDA and ROS levels （P<0.05）. In the control group， mitochondria in the substantia nigra displayed normal morphology without obvious blurred membrane structures or vacuolar degeneration. The PD group presented mitochondrial swelling， disordered cristae and vacuolar changes， whereas these mitochondrial pathological alterations were alleviated in the GCs group. Compared with the control group， the protein levels of TH， Nrf2 and HO-1 were significantly downregulated， while Keap-1 protein expression was markedly upregulated in the PD group （P<0.01）. Compared with the PD group， the GCs group showed significant upregulation of TH， Nrf2 and HO-1 protein levels and a notable reduction in Keap-1 protein level （P<0.05）. ConclusionGCs ameliorate motor dysfunction and attenuate dopaminergic neuronal and mitochondrial damage in MPTP-induced PD model mice. These effects may be associated with modulation of Nrf2/HO-1 pathway-related protein expression， enhancement of antioxidant capacity， and alleviation of oxidative stress.

ObjectiveTo investigate the effects of Hei Xiaoyaosan on neuroinflammation in APP/PS1 mice and decipher the mechanism based on the C-X3-C chemokine ligand 1 （CX3CL1）-CX3CL1 receptor 1 （CX3CR1） signaling axis. MethodsSixty 16-week-old male APP/PS1 mice were selected and acclimatized for one week， and they were then randomly allocated into a model group， a CX3CL1 group （bilateral hippocampal injection of CX3CL1 at 0.5 g·L^-1）， and high-， medium-， and low-dose （22.10， 11.05， and 5.53 g·kg^-1， respectively） Hei Xiaoyaosan groups， with 12 mice in each group. Twelve age-matched male C57BL/6J mice served as the blank group （bilateral hippocampal injection of an equal volume of PBS）. The high-， medium-， and low-dose Hei Xiaoyaosan groups received corresponding drugs via gavage， while the blank group received an equal volume of normal saline， with an intervention period of 90 days. Morris water maze was used to assess learning and memory abilities. Nissl staining was performed to observe the pathological changes in neurons of the hippocampal CA1 region. Immunohistochemistry was adopted to detect amyloid-β_1-42 （Aβ_1-42） deposition in the hippocampal CA1 region. The immunofluorescence assay was employed to detect the expression of M1 and M2 microglial markers， including cluster of differentiation 86 （CD86）/ionized calcium-binding adapter molecule 1 （Iba-1） and arginase-1 （Arg1）/Iba1. Enzyme-linked immunosorbent assay （ELISA） was employed to measure the levels of interleukin-8 （IL-8） and interleukin-13 （IL-13） in the hippocampal tissue. Western blot was employed to determine the protein levels of CX3CL1， CX3CR1， CREB-binding protein （CBP）， cyclic AMP response element-binding protein （CREB）， phosphorylated （p）-CREB， and brain-derived neurotrophic factor （BDNF） in the hippocampal tissue. ResultsCompared with the blank group， the model group exhibited prolonged escape latency on day 5 and a reduced swimming distance in the target quadrant （P<0.01）， disarrangement of hippocampal neurons， with a reduced number of cells and uneven Nissl body staining， increased CD86/Iba1 expression， decreased Arg1/Iba1 expression （P<0.01）， enhanced Aβ expression （P<0.01）， an elevated IL-8 level and a declined IL-13 level （P<0.01）， and downregulated protein levels of CX3CL1， CX3CR1， CBP， p-CREB， and BDNF （P<0.01）. Compared with the model group， all treatment groups showed shortened escape latency on day 5 and an increased swimming distance in the target quadrant （P<0.05， P<0.01）， regular arrangement of neurons with an increased number and increased Nissl bodies， reduced CD86/Iba1 expression， increased Arg1/Iba1 and decreased Aβ expression （P<0.01）， and a declined IL-8 level and an elevated IL-13 level （P<0.05， P<0.01）. In the CX3CL1 group and the high- and medium-dose Hei Xiaoyaosan groups， the relative expression levels of CX3CL1， CX3CR1， CBP， and p-CREB were upregulated （P<0.01）. In the low-dose Hei Xiaoyaosan group， the relative expression levels of CX3CL1， CX3CR1， CBP， p-CREB/CREB， and BDNF were upregulated （P<0.05， P<0.01）. ConclusionHei Xiaoyaosan can improve learning and cognitive abilities in APP/PS1 mice. Specifically， it may regulate the CX3CL1/CX3CR1 signaling axis to activate the CREB/BDNF signaling pathway for the subsequent release of BDNF， modulation of microglial polarization， reduction of inflammatory cytokine levels， and attenuation of Aβ deposition.

Objective:To examine the role of intestinal macrophages and the mechanism by which they produce reactive oxygen species (ROS) in abdominal pain induced by food antigens in mice with visceral hypersensitivity.Methods:Mouse models of visceral hypersensitivity were established by subjecting animals to acute cold restraint stress (ACRS) or acetic acid enema (AAE). Visceral sensitivity was evaluated using food antigen ovalbumin (OVA)-induced responses and rectal reflex measurements following ROS scavenging. The activity of intestinal macrophages was assessed using flow cytometry. In vitro enzyme immunoassays and in vivo imaging techniques were employed to quantify ROS levels. Furthermore, the influence of OVA on ROS levels following intestinal macrophage depletion was investigated. Cell culture experiments were conducted to investigate the effects of OVA on intestinal macrophage function and ROS production.Results:The two visceral hypersensitivity mouse models exhibited a significantly lower pain threshold compared to the control group. OVA-induced visceral hypersensitivity mice demonstrated enhanced visceral motor responses (VMRs), with an increase in abdominal ROS levels (ACRS vs. control: 62.00±7.68 vs. 19.80±2.39, P<0.001; AAE vs. control: 461.80±17.25 vs. 19.80±2.39, P<0.001). When ROS were cleared from the abdominal cavity of mice, VMRs were restored to normal levels (AAE vs. AAE+ROS: 83.50±8.72 vs. 71.66±2.67, P=0.010). In this mouse model, intestinal macrophages could be classified into CD45 Med and CD45 High subtypes based on the level of CD45 expression. In the AAE group, the expression of CD45 Med macrophages in the intestinal tract decreased (AAE vs. control: 0.121±0.026 vs. 0.194±0.021, P=0.007), whereas the expression of CD45 High macrophages increased (AAE vs. control: 0.249±0.087 vs. 0.018±0.003, P=0.027). Compared with the control group, the expression of CD11b in both types of macrophages increased significantly (CD45 Med vs. control: 39 547.00±4 422.59 vs. 4 055.67±506.05, P<0.05; CD45 High vs. control: 18 960.00±1 197.84 vs. 3 147.50±286.38, P=0.008), while the expression of F4/80 decreased (CD45 Med vs. control: 6 141.67±750.06 vs. 10 544.33±974.92, P=0.008; CD45 High vs. control: 1 291.50±119.50 vs. 4 007.50±327.39, P<0.001). These findings suggest that the activity of intestinal macrophages in visceral hypersensitivity mice is altered following OVA induction. By injecting different populations of macrophages into the peritoneal cavity of mice, it was found that compared to the AAE group, the injection of CD45 High macrophages significantly increased the VMR in mice (AAE vs. AAE CD45 High: 83.50±8.72 vs. 114.38±7.15, P<0.001), and aggravated the severity of diarrhea significantly. In vitro experiments revealed that food antigens could directly induce ROS production in macrophages. Compared with the control group, both the ACRS and AAE groups of mice exhibited significant diarrhea symptoms. In contrast, the severity of diarrhea in the Macrophages exhaust+ACRS and Macrophages exhaust+AAE groups was substantially reduced, with a significantly shortened recovery period. Additionally, compared with the AAE group, the degree of diarrhea in the AAE+ROSS group was alleviated. Conclusions:Food antigens may act on intestinal macrophages, inducing abdominal pain and diarrhea in visceral hypersensitive mice via the ROS pathway. CD45 High macrophages may play a pivotal role in this process.

Objective:To investigate the factors influencing the prognosis of critically ill patients and the predictive value of the C-reactive protein-albumin-lymphocyte (CALLY) index.Methods:A retrospective analysis was conducted on the clinical data of 122 critically ill patients admitted to Guoyao Dongfeng General Hospital affiliated with Hubei University of Medicine from June 2022 to December 2023. Patients were divided into a death group and a survival group based on their 28-day prognosis. Clinical data were compared between the two groups to analyze the factors influencing prognosis and assess the predictive value of various indicators. Normally distributed measurement data were expressed as Mean±SD, and intergroup comparisons were performed by independent samples t-test; non-normally distributed measurement data were expressed as M( Q1,Q3), and intergroup comparisons were performed by the Mann-Whitney U test. Counting data were expressed as case (%), and intergroup comparisons were performed by the χ2 test. Multivariate logistic regression was used to analyze factors influencing patient prognosis, and receiver operating characteristic (ROC) curves were plotted to analyze the predictive value of each indicator. Results:The Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ) score, blood lactate, CRP, and B-type natriuretic peptide levels in the death group were higher than those in the survival group [22 (17, 30) points vs. 17 (14, 22) points, (4.8±1.4) mmol/L vs. (3.3±1.0) mmol/L, 134 (83, 2 381) mg/L vs. 13 (10, 27) mg/L, 259 (111, 592) ng/L vs. 108 (40, 247) ng/L; Z=3.04, P=0.002; t=5.79, P<0.001; Z=8.57, P<0.001; Z=3.28, P=0.001, respectively]. Albumin, neutrophil count, lymphocyte count (LYC), and the CALLY index were lower in the death group than in the survival group [(31±5) g/L vs. (37±6) g/L, (58±9)×10 9/L vs. (63±10)×10 9/L, 0.6 (0.4, 0.8)×10 9/L vs. 1.3 (0.8, 1.7)×10 9/L, 0.03 (0.02, 0.11) vs. 0.26 (0.13, 0.49); t=6.05, P<0.001; t=3.04, P=0.003; Z=5.82, P<0.001; Z=6.52, P<0.001, respectively]. Multivariate logistic regression analysis indicated that the APACHE Ⅱ score and CRP were risk factors for poor prognosis in critically ill patients ( OR=1.349, 95% CI: 1.004-1.821, P=0.048; OR=1.006, 95% CI: 1.003-1.010, P=0.001, respectively), while LYC and the CALLY index were protective factors ( OR=0.297, 95% CI: 0.111-0.795, P=0.016; OR=0.989, 95% CI: 0.955-0.999, P=0.001, respectively). The area under the ROC curve for the CALLY index predicting 28-day mortality in critically ill patients was 0.872 (95% CI: 0.800-0.926), which was higher than that of the APACHE Ⅱ score, LYC, and CRP [0.673 (95% CI: 0.582-0.756), 0.664 (95% CI: 0.573-0.748), 0.576 (95% CI: 0.482-0.665), respectively]. The cut-off values were 0.06, 20 points, 0.8×10 9/L, and 50 mg/L, respectively. When the CALLY index was 0.06, the specificity was 97.65%, the sensitivity was 72.97%, and the Youden index was 0.706. Conclusions:The APACHE Ⅱ score, CRP, LYC, and CALLY index are all factors influencing the prognosis of critically ill patients. The CALLY index has certain predictive value, but its false negative rate is relatively high. Further combination with other indicators is needed to improve its predictive value.

BACKGROUND:The re-injury rate of the anterior cruciate ligament continues to be high and the unclear relationship between neuromuscular function and biomechanical risk factors may be one of the reasons for poor injury prevention and rehabilitation.OBJECTIVE:To evaluate the biomechanics and neuromuscular function characteristics of the knee joint during landing movements after anterior cruciate ligament reconstruction,and to further explore the effects of muscle strength,proprioception,and dynamic postural control on the risk indicators of anterior cruciate ligament injury during landing maneuver.METHODS:Twenty-six male anterior cruciate ligament reconstruction patients and 26 healthy control males at the age of 18-35 years were recruited and randomized to undergo joint kinesthesia test,Y-balance test,and isometric muscle strength tests.Kinematic and kinetic data of the knee joints during single-legged jump landing tasks were collected using an infrared motion capture system and force plates.RESULTS AND CONCLUSION:(1)Compared with the healthy control group,patients after anterior cruciate ligament reconstruction demonstrated higher knee valgus angle(P=0.021),lower hamstring muscle strength(P＜0.001),lower quadriceps muscle strength(P＜0.001)and Y-balance anterior reach distance(P＜0.001),and worse knee flexion kinesthesia(P＜0.001)and extension kinesthesia(P=0.001).(2)The predictor variables of knee extension moment were quadriceps strength and knee flexion kinesthesia(R2=0.298,P=0.007).The predictor variable of knee varus and valgus angle was hamstring strength(R2=0.117,P=0.048).The predictor variable of knee internal and external rotation angle was the hamstring-to-quadriceps peak torque ratio(R2=0.134,P=0.037).(3)The results showed that after anterior cruciate ligament reconstruction,patients still had abnormal biomechanical action patterns and neuromuscular function defects in the frontal plane of the knee joint,and elevating the muscle strength of the hamstrings,avoiding excessive quadriceps muscle strength and enhancing the proprioception of the knee joint were helpful to improve the biomechanical patterns of the sagittal plane,frontal plane and horizontal plane of the knee joint and reduce the risk of anterior cruciate ligament injury during landing maneuvers.

Peptide-based therapies have attracted considerable interest in the treatment of cancer, diabetes, bacterial infections, and neurodegenerative diseases due to their promising therapeutic properties and enhanced safety profiles. This review provides a comprehensive overview of the major trends in peptide drug discovery and development, emphasizing preclinical strategies aimed at improving peptide stability, specificity, and pharmacokinetic properties. It assesses the current applications and challenges of peptide-based drugs in these diseases, illustrating the pharmaceutical areas where peptide-based drugs demonstrate significant potential. Furthermore, this review analyzes the obstacles that must be overcome in the future, aiming to provide valuable insights and references for the continued advancement of peptide-based drugs.
Humans ; Peptides/pharmacology* ; Animals ; Neoplasms/drug therapy* ; Drug Discovery ; Neurodegenerative Diseases/drug therapy* ; Diabetes Mellitus/drug therapy*