Lung cancer stands as the primary cause of cancer-related mortalities globally, presenting a severe menace to human health. In individuals with non-small cell lung cancer (NSCLC), Kirsten rat sarcoma viral oncogene (KRAS) mutations serve as crucial oncogenic drivers. NSCLC with KRASG12C mutation is among the most prevalent subtypes. Currently, the detection methods for KRAS mutations predominantly concentrate on polymerase chain reaction (PCR) and sequencing platforms. The diverse derivative technologies of these two platforms each exhibit distinct merits and demerits in terms of testing performance and detection throughput, and find significant applications in tissue biopsy and liquid biopsy. In targeted therapies, KRASG12C targeted drugs, including Sotorasib, Adagrasib, Fulzerasib, Garsorasib, and Glecirasib, have demonstrated certain therapeutic efficacies in clinical trials and have obtained marketing approval. To tackle drug resistance and enhance patient's prognoses, combination therapeutic strategies that integrate targeted agents with chemotherapy, immune checkpoint inhibitors, Src homology region 2 domain-containing phosphatase 2 (SHP2) inhibitors, and epidermal growth factor receptor (EGFR) monoclonal antibodies have emerged. This paper systematically reviews the advancements in the diagnosis and targeted therapy of NSCLC with KRASG12C mutation, aiming to offer a reference for the selection of clinical treatment regimens and subsequent research.
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Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy* ; Lung Neoplasms/drug therapy* ; Proto-Oncogene Proteins p21(ras)/genetics* ; Mutation ; Molecular Targeted Therapy

Objective To establish and validate the diagnostic model of ferroptosis genes for acute myocardial infarction (AMI) based on bioinformatics. Methods Five AMI gene expression data were obtained from Gene Expression Omnibus (GEO), namely GSE66360, GSE48060, GSE60993, GSE83500, GSE34198. Among them, GSE66360 was used as the training set to perform differential analysis, and intersection of differential genes and ferroptosis genes was taken to obtain differentially expressed ferroptosis genes in AMI. GO and KEGG enrichment analyses were performed using Metascape website. Subsequently, random forest (RF) algorithm was used to screen out key genes with high classification performance according to the Keeny coefficient score, and artificial neural network (ANN) diagnostic model of AMI ferroptosis feature gene was constructed by model group GSE83500. The area under the receiver operating characteristic curve (AUC) of 10-fold cross-validation was used to evaluate the performance and generalization ability of the model, and 3 external independent datasets were used to verify the diagnostic performance of this model. The single sample gene set enrichment analysis was used to explore the difference in immune cell infiltration between infarcted myocardium and normal myocardium after AMI. In addition, correlation analysis between immune cells and key genes was also conducted. Finally, potential drugs that would prevent and treat AMI by regulating ferroptosis were screened out from the Coremin Medical platform. Results A total of 16 differentially expressed ferroptosis genes were obtained in the training set, GO enrichment analysis showed that they mainly participated in biological functions such as cellular response to biological stimuli and chemical stress, and regulation of interleukin 17. KEGG enrichment analysis showed that these genes were significantly enriched in NOD-like receptor signaling pathway, programmed cell necrosis, Leishmaniasis and other pathways. Four genes with good classification performance were screened out using RF algorithm, namely EPAS1, SLC7A5, FTH1, and ZFP36. The results of 10-fold cross-validation showed that the minimum AUC value was 0.746, the maximum value was 0.906, and the average value was 0.805. The AUC of the ANN model was 0.859, and the AUC values of the three independent validation sets were 0.763 (GSE48060), 0.673 (GSE60993), 0.698 (GSE34198). Immune cell infiltration found that macrophages, mast cells and monocytes were significantly active after AMI. Correlation analysis found that there were positive correlations between 4 key genes and activated dendritic cells, eosinophils and γδT cells. A total of 20 potential western medicines were predicted which could prevent and treat AMI by regulating ferroptosis, and the predicted potential Chinese medicine was mainly heat-clearing and detoxifying and blood-activating and removing blood stasis drugs. Conclusion The identified AMI ferroptosis genes by bioinformatics method have certain diagnostic significance, which provides a reference for disease diagnosis and treatment.

Standardized reporting is a crucial factor affecting the use of patient guidelines （PGs）， particularly in the reporting and presentation of recommendations. This paper introduced the current status of PG reporting， including the research on PG content and presentation formats， and provided comprehensive recommendations for PG reporting from aspects such as overall framework， recommendations， presentation format， and readability. First， the presentation of PG recommendations should include clearly defined clinical questions， recommendations and their rationale， and guidance on how patients should implement the interventions； for specific content in the PG， such as level of evidence， level of recommendation， it is recommended to explain in text the reasons for giving different levels of recommendation， i.e.， to present the logic behind giving the level of recommendation to the patient； additional information needed in the recommendation framework should be supplemented by tracing references or authoritative textbooks and literature that support the recommendations. Subsequently， the PG text should be written based on the Reporting Checklist for Public Versions of Guidelines （RIGHT-PVG） reporting framework. Finally， to enhance readability and comprehension， it is recommended to refer to the Patient Education Materials Assessment Tool （PEMAT） for translating PG content. To enhance the readability of PGs， it is suggested to present the PG content in a persona-lized and layered manner.

Since the concept of patient versions of guidelines （PVGs） was introduced into China， several PVGs have been published in China， but we found that there is a big difference between the concept of PVG at home and abroad， and the reason for this difference has not been reasonably explained， which has led to ambiguity and even misapplication of the PVG concept by guideline developers. By analyzing the background and purpose of PVGs， and the understanding of the PVG concept by domestic scholars， we proposed the term patient guidelines （PGs）. This refers to guidelines developed under the principles of evidence-based medicine， centered on health issues that concern patients， and based on the best available evidence， intended for patient use. Except for the general attribute of providing information or education， which is typical of common health education materials， PGs also provide recommendations and assist in decision-making， so PGs include both the patient versions of guidelines （PVG） as defined by the Guidelines International Network （GIN） and "patient-directed guidelines"， i.e. clinical practice guidelines resulting from the adaptation or reformulation of recommendations through clinical practice guidelines.

At present， the process and methodology of patient guidelines （PGs） development varies greatly and lacks systematic and standardised guidance. In addition to the interviews with PG developers， we have sorted out the relevant methodology for the adaptation and development of existing clinical practice guideline recommendations and facilitated expert deliberations to achieve a consensus， so as to finally put forward a proposal for guidance on the process and methodology for the development of PGs. The development of PGs can be divided into the preparation stage， the construction stage， and the completion stage in general， but the specific steps vary according to the different modes of development of PGs. The development process of Model 1 is basically the same as the patient version of the guideline development process provided by the International Guidelines Network， i.e.， team formation， screening of recommendations， guideline drafing， user testing and feedback， approval and dissemination. The developer should also first determine the need for and scope of translating the clinical practice guideline into a patient version during the preparation phase. Model 2 adds user experience and feedback to the conventional clinical practice guideline development process （forming a team， determining the scope of the PG， searching， evaluating and integrating evidence， forming recommendations， writing the guideline， and expert review）. Based on the different models， we sort out the process and methods of PG development and introduce the specific methods of PG development， including how to identify the clinical problem and how to form recommendations based on the existing clinical practice guidelines， with a view to providing reference for guideline developers and related researchers.

Lung cancer accounts for the highest proportion of cancer deaths in the world and poses a great threat to human health.About 30％to 40％of non-small cell lung cancer(NSCLC)is caused by point mutations,exon insertion and exon deletion of the epidermal growth factor receptor(EGFR).In addition to the common exon 19 deletion mutation and exon 21 L858R mutation,exon 18 G719X mutation,exon 21 L861Qmutation and exon 20 S768I mutation are the most important rare mutations.At present,the diagnostic methods for major rare mutations are mainly next-generation sequenc-ing(NGS),digital polymerase chain reaction(dPCR),droplet digital PCR(ddPCR),etc.Regarding the targeted therapy of G719X/L861Q/S768I mutant NSCLC,the first generation EGFR-tyrosine kinase inhibitors(TKIs)have poor efficacy,while the second and third generation EGFR-TKIs have similar efficacy.The novel third generation EGFR-TKIs and combina-tion therapy show a good therapeutic prospect.This article summarized the progress in the diagnosis and targeted therapy of G719X/L861Q/S768I mutant NSCLC,so as to provide reference for subsequent clinical drug use and research.

Objective To prepare a sustained-release membrane with longer adhesion time and dissolution time, and compare it with the commercially available oral ulcer membrane. Method Adhesion strength, adhesion time, swelling coefficient, dissolution time, etc. were used as the inspection indicators, and a combination of single factor inspection and analytic hierarchy process were used to screen the membrane -forming materials. The dispersion method of clotrimazole, ornidazole and borneol were investigated to prevent the drug from seed out. The method of combining orthogonal experiment and analytic hierarchy process were used to optimize the dosage of CMC-Na, PVA-1788 and glycerin; and the commercial products were compared. Results Through single-factor investigation and orthogonal experiment, the optimal ratio of excipients was selected as CMC-Na∶PVA-1788∶glycerol (3∶1∶0.08). The water-insoluble component clotrimazole, ornidazole and borneol were treated by precipitation in liquid with good effect. The best method was used to prepare the membrane. The adhesion strength was 102 g. The adhesion time was 55 min. The swelling coefficient was 1 939.52. The average dissolution time was 110 min. The appearance was white and the surface was free of bubbles, soft and elastic. The membrane forming time at 60 ℃ was 300 min and the demolding effect was better which could be completely peeled off with moderate thickness. Conclusion The oral ulcer membrane developed in this method has good appearance, comfortable use, strong adhesion, long adhesion time and dissolution time, and could stay on the ulcer surface for a long time to form physical isolation, and slowly release the drug during the dissolution process, which could play the role of long-term pain relief, antibacterial, anti-inflammatory and promote healing effects on oral ulcers.

Objective:To establish and evaluate a new real-time quality control method that can identify the random errors by using the backpropagation neural network (BPNN) algorithm and taking blood glucose test as an example.Methods:A total of 219 000 blood glucose results measured by Siemens advia 2 400 analytical system from January 2019 to July 2020 and derived from Laboratory Information System of Beijing Chaoyang Hospital Laboratory Department was regarded as the unbiased data of our study. Six deviations with different sizes were introduced to generate the corresponding biased data. With each biased data, BPNN and MovSD algorithms were used and tested, and then evaluated by traceability method and clinical method.Results:For BPNN algorithm, the block size was pre-set to 10 and the false-positive rate in all biases was within 0.1%. For MovSD, however, the optimal block size and exclusive limit were 150 and 10% separately and its false-positive rate in all biases was 0.38%, which was 0.28% higher than BPNN. Especially, for the least two error factors of 0.5 and 1, all the random errors were not detected by MovSD; for the error factor larger than 1, random errors could be detected by MovSD but the MNPed was higher than that of BPNN under all deviations. The difference was up to 91.67 times. 460 000 reference data were produced by traceability procedure. The uncertainty of BPNN algorithm evaluated by these reference data was only 0.078%.Conclusion:A real-time quality control method based on BPNN algorithm was successfully established to identify random errors in analytical phase, which was more efficient than MovSD method and provided a new idea and method for the identification of random errors in clinical practice.

Objective:To investigate the application value of establishing the differential diagnosis model of pulmonary tuberculosis using routine laboratory data.Methods:The retrospective study was conducted. The routine laboratory data of newly diagnosed patients with pulmonary tuberculosis and other pulmonary diseases in Beijng Jishuitan Hospital and Beijing Hepingli Hospital from May 2015 to November 2021were collected. According to the random numbers showed in the computer, all the 11516 patients were divided into training dataset and test dataset with a ratio of 9∶1. Four machine learning algorithms, Support Vector Machine, Random Forest, K-Nearest Neighbor and Logistic Regression, were used to build models and select features. The diagnostic accuracy of each model was verified by using the 10-fold cross-validation method and the performance of each model was evaluated by using the receptor operator of characteristic (ROC) curve.Results:Random Forest was selected as the optimal machine learning algorithm to build the best feature model in the study. According to importance scale of factors, the differential diagnosis model of pulmonary tuberculosis consisting of 37 non-specific test indexes. In the validation set and test set the accuracy and area under curve (AUC) of the models were 0.747 and 0.736, the sensitivity, specificity and accuracy were 68.03% and 68.75%, 70.91% and 67.90%, 70.30% and 68.12%, respectively.Conclusion:A key tool in the differential diagnosis model of pulmonary tuberculosis was established by routine laboratory data in combination with machine learning. The results of this study need to be further verified by more data from medical institutions.

Objective:To study the value and advantage of color Doppler and cervical multi-slice spiral CT (MSCT) in the diagnosis of cervical lymphadenopathy.Methods:A total of 130 patients with cervical lymphadenopathy diagnosed and treated in the Chenzhou First People′s Hospital from January 2019 to December 2020 were selected and received color Doppler ultrasound examination and MSCT examination. The results of pathological examination were used as the gold standard to compare the efficacy of the two methods in the differential diagnosis of benign and malignant cervical lymphadenopathy.Results:Ultrasound examination of malignant lymph nodes showed irregular boundaries, uneven internal hypoecho, and abundant blood flow signals in lymph nodes; ultrasound examination of benign lymph nodes showed uniform fine dot echo, uniform growth of endothelial medulla, clear and smooth boundary, no blood flow signal or scattered dot blood flow signal. The MSCT images of malignant lymph node showed irregular shape, blurred edge, obvious and uneven enhancement and higher rate of calcification. The aspect ratio of lymph nodes in benign lymph node was significantly higher than that in malignant lymph node (2.14 ± 0.48 vs. 1.92 ± 0.43), and the maximum blood flow velocity (V max), resistance index (RI) and blood flow (BF) in systolic period were significantly lower than those in lymph node [(21.38 ± 3.61) cm/s vs. (23.17 ± 2.55) cm/s, 0.62 ± 0.14 vs. 0.71 ± 0.17, (48.82 ± 13.51) ml/(min·100 g) vs. (65.61 ± 14.64) ml/(min·100 g)], there were statistical differences ( P<0.05). The most common blood flow types was lymphatic hilum type in benign lymph node, the proportion was 51.79% (29/56), while the most common type in malignant lymph node was marginal type and central type, the proportion was 44.59% (33/74) and 25.68% (19/74). The sensitivity, specificity, accuracy and Kappa value of ultrasound combined with MSCT in diagnosis were 92.86%, 95.95%, 94.62% and 0.890. Conclusions:Both color Doppler ultrasonography and MSCT can differentiate the benign and malignant of cervical lymph node lesions with better parameters such as lymph node imaging characteristics and blood flow distribution pattern, but the combined diagnosis has higher sensitivity, specificity and accuracy.