Gastric Cancer: 10-Year Survival after Surgery

Methods: We analyzed data of 796 consecutive GCP (age=57.1±9.4 years; tumor size=5.4±3.1 cm) radically operated (R0) and monitored in 1975-2021 (m=556, f=240; distal gastrectomies-G=461, proximal G=165, total G=170, D2 lymph node dissection=551; combined G with resection of 1-7 adjacent organs (pancreas, liver, diaphragm, esophagus, colon transversum, splenectomy, small intestine, kidney, adrenal gland, etc.)=245; D3-4 lymph node dissection=245; only surgery-S=623, adjuvant chemoimmunotherapy-AT=173: 5FU+thymalin/taktivin; T1=237, T2=220, T3=182, T4=157; N0=435, N1=109, N2=252, M0=796; G1=222, G2=164, G3=410; early GC=164, invasive GC=632; Variables selected for 10YS study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of GCP were evaluated using a log-rank test. Multivariate Cox modeling, discriminant analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence. Results: Overall life span (LS) was 2130.8±2304.3 days and cumulative 5-year survival (5YS) reached 58.4%, 10 years – 52.4%, 20 years – 40.4%. 316 GCP lived more than 5 years (LS=4316.1±2292.9 days), 169 GCP – more than 10 years (LS=5919.5±2020 days). 294 GCP died because of GC (LS=640.6±347.1 days). AT significantly improved 10YS (62.3% vs. 50.5%) (P=0.0228 by log-rank test) for GCP. Cox modeling displayed that 10YS of LCP significantly depended on: phase transition (PT) early-invasive GC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, AT, blood cell circuit, prothrombin index, hemorrhage time, residual nitrogen, age, sex, procedure type (P=0.000-0.039). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 10YS and healthy cells/CC (rank=1), PT early-invasive GC (rank=2), PT N0—N12(rank=3), erythrocytes/CC (4), thrombocytes/CC (5), monocytes/CC (6), segmented neutrophils/CC (7), eosinophils/CC (8), leucocytes/CC (9), lymphocytes/CC (10), stick neutrophils/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). Conclusions: 10-Year survival of GCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) GC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.

Non-small cell lung cancer: 10-year survival after surgery

Objective: 10-Year survival (10YS) after radical surgery for non-small cell lung cancer (LC) pa­tients (LCP) (T1-4N0-2M0) was analyzed. Methods: We analyzed data of 768 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2021 (m=660, f=108; upper lobectomies=277, lower lobectomies=177, middle lobectomies=18, bilobectomies=42, pneumonectomies=254, mediastinal lymph node dissection=768; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=193; only surgery-S=618, adjuvant chemoimmunoradiotherapy-AT=150: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=320, T2=255, T3=133, T4=60; N0=516, N1=131, N2=121, M0=768; G1=194, G2=243, G3=331; squamous=417, adenocarcinoma=301, large cell=50; early LC=214, invasive LC=554; right LC=412, left LC=356; central=290; peripheral=478. Variables selected for 10YS study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of LCP were evaluated using a log-rank test. Multivariate Cox modeling, analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence. Results: Overall life span (LS) was 2244.9±1750.3 days and cumulative 5-year survival (5YS) reached 72.9%, 10 years – 64.3%, 20 years – 43.1%. 502 LCP lived more than 5 years (LS=3128.7±1536.8 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). AT significantly improved 10YS (52.4% vs. 27.7%) (P=0.00002 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 10YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time, weight, color index (P=0.000-0.039). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 10YS and PT early-invasive LC (rank=1), thrombocytes/CC (rank=2), PT N0—N12(rank=3), segmented neutrophils/CC (4), healthy cells/CC (5), lymphocytes/CC (6), erythrocytes/CC (7), stick neutrophils/CC (8), eosinophils/CC (9), leucocytes/CC (10), monocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). Conclusions: 10-Year survival of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.

Classification of advanced methods for evaluating neurotoxicity

Purpose of review As fields such as neurotoxicity evaluation and neuro-related drug research are increasing in popularity, there is a demand for the expansion of neurotoxicity research. Currently, neurotoxicity is assessed by measuring changes in weight and behavior. However, measurement of such changes does not allow the detection of subtle and inconspicuous neurotoxicity. In this review, methods for advancing neurotoxicity research are divided into molecule-, cell-, circuit-, and animal model-based methods, and the results of previous studies assessing neurotoxicity are provided and discussed. Recent findings In coming decades, cooperation between universities, national research institutes, industrial research institutes, governments, and the private sector will become necessary when identifying alternative methods for neurotoxicity evaluation, which is a current goal related to improving neurotoxicity assessment and an appropriate approach to neurotoxicity prediction. Many methods for measuring neurotoxicity in the field of neuroscience have recently been reported. This paper classifies the supplementary and complementary experimental measures for evaluating neurotoxicity.

Lymph node metastases of gastric cancer and blood cell circuit.

e16024 Background: Significance of blood cell circuit in terms of detection of gastric cancer (GC) patients (GCP) with lymph node metastases was investigated. Methods: We analyzed data of 793 consecutive GCP (age = 57±9.4 years; tumor size = 5.4±3.1 cm) radically operated (R0) and monitored in 1975-2021 (m = 555, f = 238; distal gastrectomies = 460, proximal gastrectomies = 163, total gastrectomies = 170, combined gastrectomies with resection of pancreas, liver, diaphragm, colon transversum, esophagus, duodenum, splenectomy, small intestine, kidney, adrenal gland = 244; D2-lymphadenectomy = 513, D3-4 = 280; T1 = 235, T2 = 220, T3 = 182, T4 = 156; N0 = 433, N1 = 109, N2 = 251; G1 = 222, G2 = 162, G3 = 409; early GC = 162, invasive = 631; only surgery = 621, adjuvant chemoimmunotherapy-AT = 172 (5-FU+thymalin/taktivin). Variables selected for study were input levels of blood cell circuit, sex, age, TNMG. Differences between groups were evaluated using discriminant analysis, clustering, nonlinear estimation, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks computing. Results: It was revealed that separation of GCP with lymph node metastases (n = 360) from GCP without metastases (n = 433) significantly depended on: eosinophils (%, abs, total), thrombocytes (abs, total), ESS, Hb, erythrocytes (abs), residual nitrogen, protein, cell ratio factors (CRF) (ratio between cancer cells- CC and blood cells subpopulations), T, G, tumor size, histology, tumor growth, blood group, procedures type (P = 0.043-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of lymph node metastases and CRF: thrombocytes/CC (rank = 1), healthy cells/CC (2), erythrocytes/CC (3), monocytes/CC (4), segmented neutrophils/CC (5), lymphocytes/CC (6), leucocytes/CC (7), eosinophils/CC (8), stick neutrophils/CC (9). Correct classification N0—N12 was 99.9% by neural networks computing (area under ROC curve = 1.0; error = 0.0). Conclusions: Lymph node metastases of gastric cancer significantly depended on blood cell circuit.

Current Input Pixel-Level ADC with High SNR and Wide Dynamic Range for a Microbolometer

A readout circuit incorporating a pixel-level analog-to-digital converter (ADC) is studied for two-dimensional medium wavelength infrared microbolometer arrays. The signal-to-noise ratio (SNR) and charge handling capacity of the unit cell circuit are improved by using the current input pixel-level ADC. The charge handling capacity of the integrator is appropriately extended to maximize the integration time regardless of the magnitude of the input current and low power supply voltage. The readout circuit was fabricated using a 0.35-μm 2-poly 4-metal CMOS process for a 640 × 512 array with a pixel size of 40 μm × 40 μm. The peak SNR and dynamic range are 77.1 and 80.1 dB, respectively, with a power consumption of 0.62 μW per pixel.