AIM:To analyze differential proteins associated with the pathogenesis of dry eye(DE)using bioinformatics methods, in order to reveal their potential molecular mechanisms.METHODS: Articles published in PubMed and EMBASE databases from the inception of the database to August 31, 2023, that used proteomic methods to detect protein expression in clinical samples of dry eye were searched. Differential proteins were selected and further analyzed using the STRING database and Cytoscape software for hub gene screening and module analysis. Protein-protein interaction(PPI)analysis, gene ontology(GO)functional annotation, and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis were performed.RESULTS: A total of 21 articles were included, identifying 74 differentially expressed proteins. The most frequently occurring differential proteins were calgranulin A(SA1008), lipocalin-1(LCN1), lysozyme C(LYZ), mammaglobin-B(SCGB2A1), proline-rich protein 4(PRR4), transferrin(TF), and calgranulinB(S100A9). The top 10 hub genes were serum albumin(ALB), tumor necrosis factor(TNF), interleukin 6(IL6), IL1B, IL8, matrix metalloproteinase 9(MMP9), alpha-1-antitrypsin(SERPINA1), IL10, complement component 3(C3), and lactotransferrin(LTF). Module analysis suggested MMP9 and PRR4 as seed genes. KEGG analysis showed that differential proteins were mainly enriched in the IL17 signaling pathway(61.9%).CONCLUSION: The results reveal potential molecular targets and pathways for DE and confirm the association between the pathogenesis of DE and inflammation. Further in-depth research is needed to confirm the significance of these biomarkers in clinical practice.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.

AIM: To delineate the specific mutation responsible for retinitis pigmentosa(RP)in a Yi pedigree, and to analyze the correlation of RHO gene mutation with clinical phenotype.METHODS:A comprehensive clinical evaluation was conducted on the proband diagnosed with RP and other familial members, complemented by a thorough ophthalmic examination. Peripheral blood samples were obtained from the proband and familial members, from which genomic DNA was extracte. Subsequent whole exome sequencing(WES)was employed to identify the variant genes in the proband. The identified variant gene was validated through Sanger sequencing, then an in-depth analysis of the mutation genes was carried out using genetic databases to ascertain the pathogenic mutation sites. Furthermore, an exhaustive analysis was performed to delineate the genotype and phenotype characteristics.RESULTS:The RP pedigree encompasses 5 generations with 42 members, including 19 males and 23 females. A total of 13 cases of RP were identified, consisting of 4 males and 9 females, which conforms to the autosomal dominant inheritance pattern. The clinical features of this family include an early onset age, rapid progression, and a more severe condition. The patients were found to have night blindness around 6 years old, representing the earliest reported case of night blindness in RP families. The retina was manifested by progressive osteocytoid pigmentation of the fundus, a reduced visual field, and significantly decreased or even vanished a and b amplitudes of ERG. The combined results of WES and Sanger sequencing indicated that the proband had a heterozygous missense mutation of the RHO gene c.1040C>T:p.P347L, where the 1 040 base C of cDNA was replaced by T, causing codon 347 to encode leucine instead of proline. Interestingly, this mutation has not been reported in the Chinese population.CONCLUSION:This study confirmed that the mutant gene of RP in a Yi nationality pedigree was RHO(c.1040C>T). This variant leads to the change of codon 347 from encoding proline to encoding leucine, resulting in a severe clinical phenotype among family members. This study provides a certain molecular, clinical, and genetic basis for genetic counseling and gene diagnosis of RHO.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

OBJECTIVE To analyze the occurrence characteristics and risk factors of adverse drug reactions （ADR） of gemcitabine for injection in national centralized volume-based procurement （hereinafter referred to as “centralized procurement”）， and provide reference for clinical safe drug use. METHODS A retrospective study was conducted to collect the relevant case reports of gemcitabine for injection reported to the National Adverse Drug Reaction Monitoring System by Inner Mongolia Autonomous Region from January 2022 to December 2023； basic information of patients， drug use status， patient outcomes， rational drug use and other information were collected， and the occurrence characteristics of ADRs with leukopenia， myelosuppression， neutropenia， thrombocytopenia and liver dysfunction were analyzed. Univariate analysis and multivariate Logistic regression were used to analyze the correlation of gender， age， combination of antitumor drugs， original malignant tumor and drug dose with ADR. RESULTS A total of 315 cases reports （315 patients） of gemcitabine-induced ADR were included in this study， with a male-to-female ratio of 1.42∶1 and age of （61.17±9.13） years. The primary malignant tumor was pancreatic cancer （73 cases， 23.17%）. Leukopenia， myelosuppression and nausea were the most common ADR， followed by neutropenia， thrombocytopenia， liver dysfunction and so on. The severity grade of ADR was mainly 1-2， and the outcome of most ADR was good. Multivariate Logistic regression analysis showed that combination of antitumor drugs was a risk factor for myelosuppression and neutropenia （RR＝2.154， 95%CI： 1.218- 3.807， P＝0.008； RR＝3.099， 95%CI： 1.240-7.744， P＝0.016）； gender （female） was a risk factor for leukopenia and liver dysfunction （RR＝0.508， 95%CI： 0.302-0.853， P＝0.010； RR＝0.301， 95%CI： 0.102-0.887， P＝0.029）. In terms of drug use rationality， there were 143 cases （45.40%） of drug 126.com use in accordance with the indications of the label， and 172 cases （54.60%） of off-label drug use. Among them， the primary malignant tumors were bladder cancer， bile duct cancer and ovarian cancer， which ranked the top three off-label drug use. CONCLUSIONS The ADR caused by gemcitabine in Inner Mongolia is mainly in the blood and digestive systems. The severity of ADRs is mainly classified as 1-2 levels， and most ADRs have good outcomes. Gender （female） and combination medication are risk factors for gemcitabine-induced ADR. Appropriate chemotherapy regimen should be selected according to the patient’s condition and physical condition， and ADR monitoring in blood and digestive systems should be strengthened during medication of gemcitabine.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

Osteoporosis is a common senile bone metabolism disease， clinically characterized by decreased bone mass， destruction of bone microstructure， increased bone fragility， and easy fracture. It tends to occur in the elderly and postmenopausal women， seriously threatening the quality of life and physical and mental health of the elderly. At present， the treatment of osteoporosis is mainly based on oral western medicines， such as calcium， Vitamin D， and bisphosphonates. Still， there are drawbacks such as a long medication cycle and many adverse reactions. In recent years， due to the advantages of multi-component， multi-pathway， and multi-target， some traditional Chinese medicines and effective ingredients can regulate the osteogenic and osteoclastic differentiation process in both directions and are widely used in the prevention and treatment of osteoporosis. Hippophae rhamnoides is a commonly used herbal medicine， and its fruits are rich in flavonoids， polyphenols， fatty acids， vitamins， and trace elements， which have been proven to have a good anti-osteoporosis effect. Isorhamnetin is the main effective ingredient of Hippophae rhamnoides fruits， which has many pharmacological effects such as anti-inflammation， anti-oxidative stress， anti-aging， and anti-tumor. Studies have shown that isorhamnetin can participate in the regulation of bone metabolism and has a good anti-osteoporosis effect. However， the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis have not been systematically summarized. Therefore， this paper reviewed the pharmacological effects and related mechanisms of isorhamnetin against osteoporosis by referring to relevant literature to provide more basis for the development and application of isorhamnetin.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.

ObjectiveTo explore the distribution pattern of tongue image characteristics in patients with glucolipid metabolic disorders and its main syndromes. MethodsA total of 841 patients with glucolipid metabolic disorders （disease group）， and 380 healthy subjects （control group） were included. The disease group was classified into three syndrome types： 283 cases of liver depression and spleen deficiency syndrome， 311 cases of phlegm-dampness obstruction syndrome， and 247 cases of qi stagnation and blood stasis syndrome. Tongue image data were collected using the TFDA-1 Tongue Diagnosis Instrument， and the TDAS V3.0 software was used to analyze the color， texture， and morphological features of the tongue body （TB） and tongue coating （TC） in patents with different syndromes of disease group （including lightness （L）， red-green axis （a）， yellow-blue axis （b）， luminance （Y）， difference between red signal and brightness （Cr）， difference between blue signal and brightness （Cb）， contrast （CON）， angular second moment （ASM）， entropy （ENT）， mean value （MEAN）， tongue coating area/tongue surface area （perAll）， and tongue coating area/non-coated area （perPart））. Logistic regression analysis was conducted to identify influencing factors for different syndrome types of glucolipid metabolic disorders. ResultsThe tongue body indicators TB-L， TB-Y， and TB-Cb in the disease group were significantly higher than those in the control group， while TB-a， TB-b， and TB-Cr were significantly lower. The tongue coating indicators TC-L， TC-Y， TC-Cb， perAll， and perPart in the disease group were significantly higher than those in the control group， while TC-a， TC-b， and TC-Cr were significantly lower （P＜0.05）. Comparing with the different syndromes in disease group， the TB-L and TB-Y of the liver depression and spleen deficiency syndrome， and the phlegm-damp obstruction syndrome were higher than those of the qi stagnation and blood stasis syndrome； the TB-a and TB-Cr of the phlegm-damp obstruction syndrome were lower than those of the qi stagnation and blood stasis syndrome； the perAll of the phlegm-damp obstruction syndrome was higher than that of the qi stagnation and blood stasis syndrome （P＜0.05）. In the analysis of the morphological characteristics of tongue signs， more spotted tongue in disease group compared with control group， more teeth-marked tongue in liver depression and spleen deficiency syndrome than the other two syndromes， more greasy coating in phlegm-damp obstruction syndrome， and more stasis spots of tongue in qi stagnation and blood stasis syndrome （P＜0.05）. Logistic regression analysis identified that greasy coating， spotted tongue， stasis spots of tongue， tooth-marked tongue， perAll， and TB-Cb are the influencing factors of liver depression and spleen deficiency syndrome； greasy coating， tooth-marked tongue， TC-Cb， and TC-Cr are the influencing factors of phlegm-damp obstruction syndrome； cracked tongue， stasis spots of tongue， tooth-marked tongue， and TB-Y are the influencing factors of qi stagnation and blood stasis syndrome （P＜0.05）. ConclusionCompared to healthy individuals， patients with glycolipid metabolic disorder have darker tongue color and thicker， greasy tongue coating. Glycolipid metabolic disorder patients of liver depression and spleen deficiency syndrome exhibit a reddish tongue with finer textures and more tooth marks； patients of phlegm-damp obstruction syndrome have lighter tongue coating with a coarser texture and a higher prevalence of greasy coating； patients of qi stagnation and blood stasis syndrome display lower tongue brightness with a higher prevalence of blood stasis spots.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.