A selective and sensitive competitive enzyme-linked immunosorbent assay (ELISA) method was developed and validated for the quantification of erlotinib in 50μL of samples of human serum. Anti-erlotinib serum was obtained by immunizing mice with an antigen conjugated with bovine serum albumin and 3,4-bis(2-methoxyethoxy)benzoic acid using the N-succinimidyl ester method. Enzyme labeling of erlotinib with horseradish peroxidase was similarly performed using 3,4-bis(2-methoxyethoxy)benzoic acid. A simple competitive ELISA for erlotinib was developed using the principle of direct competition between erlotinib and the enzyme marker for anti-erlotinib antibody, which had been immobilized on the plastic surface of a microtiter plate. Serum erlotinib concentrations lower than 40 ng/mL were reproducibly measurable using the ELISA. This ELISA was specific to erlotinib and showed very slight cross-reactivity (6.7％) with a major metabolite, O-desmethyl erlotinib. Using this assay, drug levels were easily measured in the blood of mice after oral administration of erlotinib at a single dose of 30 mg/kg. ELISA should be used as a valuable tool for therapeutic drug monitoring and in pharmacokinetic studies of erlotinib.

Afatinib is an oral tyrosine kinase inhibitor (TKI) approved for treating advanced non-small cell lung cancer. It is necessary to develop a simple quantification method for TKIs in order to facilitate therapeutic drug monitoring (TDM) in clinical settings. This study sought to develop a simple and sensitive com-petitive enzyme-linked immunosorbent assay (ELISA) to quantify afatinib in plasma for routine phar-macokinetic applications. An anti-afatinib antibody was obtained using (S)-N-4-(3-chloro-4-fluor-ophenyl)-7-(tetrahydrofuran-3-yloxy)-quinazoline-4,6-diamine (CTQD), which has the same sub-structure as afatinib, as a hapten. Enzyme labeling of afatinib with horseradish peroxidase was similarly performed using CTQD. A simple competitive ELISA for afatinib was developed based on the principle of direct competition between afatinib and the enzyme marker for the anti-afatinib antibody, which had been immobilized on the plastic surface of a microtiter plate. Plasma afatinib concentrations below the limit of quantification of 30 pg/mL were reproducibly measurable. Also, the values of plasma afatinib levels measured from 20 patients were comparable with those measured by high-performance liquid chromatography, and there was a strong correlation between the values determined by both methods (Y = 0.976X – 0.207, r = 0.975). As indicated by its specificity and sensitivity, this newly developed ELISA for afatinib is an important tool for TDM and studies of the pharmacokinetics of afatinib.

An investigation was performed about clinical histories before hospitalization in 1142 cases of gastric cancer during 16 years from 1969 to 1984.
The average term from onset of the disease to hospitalization was 4.53 months which tends to decrease becoming 3.49 months in the latest 5 years. The patients had visited 0.72 other doctor in average before coming to our hospital, 0.35 in early cancer cases and 0.83 in advanced cases. The sources of patients of our surgery were as follows ; 60.5% were introduced from medical department of our hospital, 20.2% were introduced from other clinics or hospitals, 10.6% visited our surgical department directly, and 8.7% came to us after visiting one or some other doctors. The rate of early cancer cases were high and unresectable cases were low relatively in cases from our medical department and direct visitors to our surgical department.
The causative factors of delay of hospitalization more than one month were considered from both sides of patient and doctor. The results were ; no delay 55.3%, delay due to patient's fault 28.2%, delay due to doctor's fault 19.9%. The delay of hospitalization due to either side's fault was one factor of decreasing early cancers and increasing advanced cases. Among those with no delay, however, 22.6% were unresectable cases. Gastric cancers are too malignant to be cured by visiting hospitals with complaints. Gastric mass survey among symptomeless people is the only reasonable way to come out of this difficult situation.

BACKGROUND/AIMS: Diverticular bleeding can occasionally cause massive bleeding that requires urgent colonoscopy (CS) and treatment. The aim of this study was to identify significant risk factors for colonic diverticular hemorrhage. METHODS: Between January 2009 and December 2012, 26,602 patients underwent CS at our institution. One hundred twenty-three patients underwent an urgent CS due to acute lower gastrointestinal hemorrhage. Seventy-two patients were diagnosed with colonic diverticular hemorrhage. One hundred forty-nine age- and sex-matched controls were selected from the patients with nonbleeding diverticula who underwent CS during the same period. The relationship of risk factors to diverticular bleeding was compared between the cases and controls. RESULTS: Uni- and multivariate conditional logistic regression analyses demonstrated that the use of nonsteroidal anti-inflammatory drugs (odds ratio [OR], 14.70; 95% confidence interval [CI], 3.89 to 55.80; p<0.0001), as well as the presence of cerebrovascular disease (OR, 8.66; 95% CI, 2.33 to 32.10; p=0.00126), and hyperuricemia (OR, 15.5; 95% CI, 1.74 to 138.00; p=0.014) remained statistically significant predictors of diverticular bleeding. CONCLUSIONS: Nonsteroidal anti-inflammatory drugs, cerebrovascular disease and hyperuricemia were significant risks for colonic diverticular hemorrhage. The knowledge obtained from this study may provide some insight into the diagnostic process for patients with lower gastrointestinal bleeding.
Adult ; Aged ; Aged, 80 and over ; Anti-Inflammatory Agents, Non-Steroidal/adverse effects ; Case-Control Studies ; Cerebrovascular Disorders/complications ; Colonic Diseases/*etiology/surgery ; Colonoscopy ; Diverticulum, Colon/*complications/pathology/surgery ; Female ; Gastrointestinal Hemorrhage/*etiology/surgery ; Humans ; Hyperuricemia/complications ; Logistic Models ; Male ; Middle Aged ; Retrospective Studies ; Risk Factors

Europe has a long history with its own traditional medicines. In Germany, the practice of traditional European and Asian medicine along with modern medicine is called Integrative Medicine. The pain clinics at Munich University, TCM Klinik Bad Kotzting, Immanuel Klankenhaus and Zen Haus Klinik are well-known centers of Integrative Medicine in Germany. We visited these hospitals and clinics and report on the state of their treatment.
Four-week programs in chronic pain, traditional Chinese medicine, natural therapy, and traditional Japanese medicine with aromatherapy are given at these facilities. Moreover, Complementary and Alternative medicines are widely covered by public or private insurance. And one reason for the spread of Integrative Medicine may be these social conditions, in addition to historical background.

Submucosal invasive (T1) colorectal cancer is a significant clinical management challenge, with an estimated 10% of patients developing extraintestinal lymph node metastasis. This condition necessitates surgical resection along with lymph node dissection to achieve a curative outcome. Thus, the precise preoperative assessment of lymph node metastasis risk is crucial to guide treatment decisions after endoscopic resection. Contemporary clinical guidelines strive to identify a low-risk cohort for whom endoscopic resection will suffice, applying stringent criteria to maximize patient safety. Those failing to meet these criteria are often recommended for surgical resection, with its associated mortality risks although it may still include patients with a low risk of metastasis. In the quest to enhance the precision of preoperative lymph node metastasis risk prediction, innovative models leveraging artificial intelligence or nomograms are being developed. Nevertheless, the debate over the ideal sensitivity and specificity for such models persists, with no consensus on target metrics. This review puts forth postoperative mortality rates as a practical benchmark for the sensitivity of predictive models. We underscore the importance of this method and advocate for research to amass data on surgical mortality in T1 colorectal cancer. Establishing specific benchmarks for predictive accuracy in lymph node metastasis risk assessment will hopefully optimize the treatment of T1 colorectal cancer.

With the widely spreading population-based screening programs for colorectal cancer and recent improvements in endoscopic diagnosis, the number of endoscopic resections in subjects with T1 colorectal cancer has been increasing. Some reports suggest that endoscopic resection prior to surgical resection of T1 colorectal cancer has no adverse effect on prognosis and contributes to this tendency. The decision on the need for surgical resection as an additional treatment after endoscopic resection of T1 colorectal cancer should be made according to the metastasis risk to lymph nodes based on histopathological findings. Because lymph node metastasis occurs in approximately 10% of patients with T1 colorectal cancer according to current international guidelines, the remaining 90% of patients may be at an increased risk of surgical resection and associated postoperative mortality, with no clinical benefit derived from unnecessary surgical resection. Although a more accurate prediction system for lymph node metastasis is needed to solve this problem, risk stratification for lymph node metastasis remains controversial. In this review, we focus on the current status of risk stratification of T1 colorectal cancer metastasis to lymph nodes and outline future perspectives.

Submucosal invasive (T1) colorectal cancer is a significant clinical management challenge, with an estimated 10% of patients developing extraintestinal lymph node metastasis. This condition necessitates surgical resection along with lymph node dissection to achieve a curative outcome. Thus, the precise preoperative assessment of lymph node metastasis risk is crucial to guide treatment decisions after endoscopic resection. Contemporary clinical guidelines strive to identify a low-risk cohort for whom endoscopic resection will suffice, applying stringent criteria to maximize patient safety. Those failing to meet these criteria are often recommended for surgical resection, with its associated mortality risks although it may still include patients with a low risk of metastasis. In the quest to enhance the precision of preoperative lymph node metastasis risk prediction, innovative models leveraging artificial intelligence or nomograms are being developed. Nevertheless, the debate over the ideal sensitivity and specificity for such models persists, with no consensus on target metrics. This review puts forth postoperative mortality rates as a practical benchmark for the sensitivity of predictive models. We underscore the importance of this method and advocate for research to amass data on surgical mortality in T1 colorectal cancer. Establishing specific benchmarks for predictive accuracy in lymph node metastasis risk assessment will hopefully optimize the treatment of T1 colorectal cancer.

Submucosal invasive (T1) colorectal cancer is a significant clinical management challenge, with an estimated 10% of patients developing extraintestinal lymph node metastasis. This condition necessitates surgical resection along with lymph node dissection to achieve a curative outcome. Thus, the precise preoperative assessment of lymph node metastasis risk is crucial to guide treatment decisions after endoscopic resection. Contemporary clinical guidelines strive to identify a low-risk cohort for whom endoscopic resection will suffice, applying stringent criteria to maximize patient safety. Those failing to meet these criteria are often recommended for surgical resection, with its associated mortality risks although it may still include patients with a low risk of metastasis. In the quest to enhance the precision of preoperative lymph node metastasis risk prediction, innovative models leveraging artificial intelligence or nomograms are being developed. Nevertheless, the debate over the ideal sensitivity and specificity for such models persists, with no consensus on target metrics. This review puts forth postoperative mortality rates as a practical benchmark for the sensitivity of predictive models. We underscore the importance of this method and advocate for research to amass data on surgical mortality in T1 colorectal cancer. Establishing specific benchmarks for predictive accuracy in lymph node metastasis risk assessment will hopefully optimize the treatment of T1 colorectal cancer.

Submucosal invasive (T1) colorectal cancer is a significant clinical management challenge, with an estimated 10% of patients developing extraintestinal lymph node metastasis. This condition necessitates surgical resection along with lymph node dissection to achieve a curative outcome. Thus, the precise preoperative assessment of lymph node metastasis risk is crucial to guide treatment decisions after endoscopic resection. Contemporary clinical guidelines strive to identify a low-risk cohort for whom endoscopic resection will suffice, applying stringent criteria to maximize patient safety. Those failing to meet these criteria are often recommended for surgical resection, with its associated mortality risks although it may still include patients with a low risk of metastasis. In the quest to enhance the precision of preoperative lymph node metastasis risk prediction, innovative models leveraging artificial intelligence or nomograms are being developed. Nevertheless, the debate over the ideal sensitivity and specificity for such models persists, with no consensus on target metrics. This review puts forth postoperative mortality rates as a practical benchmark for the sensitivity of predictive models. We underscore the importance of this method and advocate for research to amass data on surgical mortality in T1 colorectal cancer. Establishing specific benchmarks for predictive accuracy in lymph node metastasis risk assessment will hopefully optimize the treatment of T1 colorectal cancer.