Oct-4 Expression Maintained Cancer Stem-Like Properties in Lung Cancer-Derived CD133-Positive Cells

CD133 (prominin-1), a 5-transmembrane glycoprotein, has recently been considered to be an important marker that represents the subset population of cancer stem-like cells. Herein we report the isolation of CD133-positive cells (LC-CD133+) and CD133-negative cells (LC-CD133−) from tissue samples of ten patients with non-small cell lung cancer (LC) and five LC cell lines. LC-CD133+ displayed higher Oct-4 expressions with the ability to self-renew and may represent a reservoir with proliferative potential for generating lung cancer cells. Furthermore, LC-CD133+, unlike LC-CD133−, highly co-expressed the multiple drug-resistant marker ABCG2 and showed significant resistance to chemotherapy agents (i.e., cisplatin, etoposide, doxorubicin, and paclitaxel) and radiotherapy. The treatment of Oct-4 siRNA with lentiviral vector can specifically block the capability of LC-CD133+ to form spheres and can further facilitate LC-CD133+ to differentiate into LC-CD133−. In addition, knock-down of Oct-4 expression in LC-CD133+ can significantly inhibit the abilities of tumor invasion and colony formation, and increase apoptotic activities of caspase 3 and poly (ADP-ribose) polymerase (PARP). Finally, in vitro and in vivo studies further confirm that the treatment effect of chemoradiotherapy for LC-CD133+ can be improved by the treatment of Oct-4 siRNA. In conclusion, we demonstrated that Oct-4 expression plays a crucial role in maintaining the self-renewing, cancer stem-like, and chemoradioresistant properties of LC-CD133+. Future research is warranted regarding the up-regulated expression of Oct-4 in LC-CD133+ and malignant lung cancer

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

[[alternative]]Postmodern Agriculture: A Perspective From Permaculture and Slow Food Movement

[[abstract]]樸門永續設計和慢食運動都是知名的國際運動，兩者異口同聲反對工業化、反對跨國企業，同時支持傳統生活方式。跨國速食文化除了衝擊傳統飲食，對農業生產也發生巨大影響。慢食運動認為，唯有教育消費者正確的飲食習慣，才是改變農民生產方式的關鍵因素；樸門永續設計則是由農家著眼，教育農民如何有效率地兼顧生產、生計、與生活。兩者理念及推行方式的比較是本文研究的重點。[[abstract]]Permaculture and the Slow Food movement are well-known international movements. Both of them fight against industrialization and globalization, while supporting traditional ways of life. In addition to the impact on traditional diet, multinational fast food has also undergone a tremendous influence on agricultural production. Slow Food Movement believes that to change the way farmers make production, the proper education of diet plays as the key; Permaculture, on the other hand, gears towards the education of farmers on managing production, livelihood,and life efficiently. Comparison between the concepts and the implementation approaches is discussed in this study

Smoothed Lexis Diagrams With Applications to Lung and Breast Cancer Trends in Taiwan

<div><p>Cancer surveillance research often begins with a rate matrix, also called a Lexis diagram, of cancer incidence derived from cancer registry and census data. Lexis diagrams with 3- or 5-year intervals for age group and for calendar year of diagnosis are often considered. This simple smoothing approach suffers from a significant limitation; important details useful in studying time trends may be lost in the averaging process involved in generating a summary rate. This article constructs a smoothed Lexis diagram and indicates its use in cancer surveillance research. Specifically, we use a Poisson model to describe the relationship between the number of new cases, the number of people at risk, and a smoothly varying incidence rate for the study of the incidence rate function. Based on the Poisson model, we use the standard Lexis diagram to introduce priors through the coefficients of Bernstein polynomials and propose a Bayesian approach to construct a smoothed Lexis diagram for the study of the effects of age, period, and cohort on incidence rates in terms of straightforward graphical displays. These include the age-specific rates by year of birth, age-specific rates by year of diagnosis, year-specific rates by age of diagnosis, and cohort-specific rates by age of diagnosis. We illustrate our approach by studying the trends in lung and breast cancer incidence in Taiwan. We find that for nearly every age group the incidence rates for lung adenocarcinoma and female invasive breast cancer increased rapidly in the past two decades and those for male lung squamous cell carcinoma started to decrease, which is consistent with the decline in the male smoking rate that began in 1985. Since the analyses indicate strong age, period, and cohort effects, it seems that both lung cancer and breast cancer will become more important public health problems in Taiwan. Supplementary materials for this article are available online.</p></div

SHORT-TERM FREE-FALL LANDING CAUSES REDUCED BONE SIZE AND BENDING ENERGY IN FEMORA OF GROWING RATS

The purpose of this study was to determine the effects of a mechanical loading course (short-term free-fall landing) on femoral geometry and biomechanical properties in growing rats. Thirty-two female Wistar rats (7-week-old) were randomly assigned to three groups: L30 (n = 11), L10 (n = 11) and CON (n = 10) groups. Animals in the L10 and L30 groups were subjected to a 5-day free-fall landing program in which animals were dropped from a height of 40cm 10 and 30 times per day, respectively. Landing ground reaction force (GRF) was measured on the 1st and 5th days of landing training. All animals were subjected to two fluorescent labeling injections on the days before and after the 5-day landing training. Three days after the last labeling injection, animals were sacrificed under deep anesthesia. Methods of dynamic histomorphometry, tissue geometry and tissue biomechanical measurements were used to investigate the response in femora. A significant decrease in peak GRF in the hind-limb was shown from day 1 to day 5. No significant difference was shown among groups in dynamic histomorphometry. Biomechanical property analyses showed significantly lower maximal energy and post-yield energy in the L10 and L30 groups as compared to the CON group (p < 0.05). Moreover, geometric measurements revealed that cross-sectional cortical areas and thicknesses were significantly lower in landing groups than in the CON group. Short-term (5-day) free-fall landing training resulted in minor compromised long bone tissue, as shown by reduced bending energy and cortical bone area but not in other mechanical properties or tissue measurements (e.g. weights and length) of growing female rats. Further studies would be valuable to investigate whether this compromised bone material represents the existence of a latency period in the adaptation of bone material to external mechanical loading

Inhibition of CDCP1 by 8‐isopentenylnaringenin synergizes with EGFR inhibitors in lung cancer treatment

CUB domain‐containing protein 1 (CDCP1) contributes to epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) resistance by regulating EGFR signaling pathways and is a potential target in lung cancer treatment. This study aims to identify a CDCP1 reducer that synergistically improves TKI treatment. Utilizing a high‐throughput drug screening system, a phytoestrogen 8‐isopentenylnaringenin (8PN) was identified. Upon 8PN treatment, CDCP1 protein levels and malignant features were reduced. 8PN exposure caused the accumulation of lung cancer cells in G0/G1 phase and increased the proportion of senescent cells. In EGFR TKI‐resistant lung cancer cells, the combination of 8PN and TKI synergistically reduced cell malignance, inhibited downstream EGFR pathway signaling, and exerted additive effects on cell death. Moreover, combination therapy effectively reduced tumor growth and enhanced tumor necrosis in tumor xenograft mice models. Mechanistically, 8PN increased interleukin (IL)6 and IL8 expression, induced neutrophil infiltration, and enhanced neutrophil‐mediated cytotoxicity to attenuate lung cancer cell growth. In conclusion, 8PN enhances the anticancer efficacy of EGFR TKI on lung cancer and triggers neutrophil‐dependent necrosis, highlighting the potential to overcome TKI resistance in lung cancer patients who have EGFR mutation