4,324 research outputs found
Ideas in ecology
Journal ArticleThe word "ecology" means different things to different people. For example, during the last 25 years or so the word has been used to label attitudes, life-styles, consumer goods, political parties, and college courses. In the 1960s one university renamed its "Home Economics" course "Home Ecology." (But our own biology department reacted to the growing visibility of its conventional "Ecology" course by renaming it "Population Biology.") It is often said that Thoreau coined the word "ecology." He certainly ought to have done so, given the Rousseauesque yearnings that surround the word, and this may be why the myth lives on, even though it stems from a 1958 misreading of the word "geology" as "ecology" in one of his letters (James 1985). The German biologist Haeckel was actually the first to use the word "Oecologie," in 1866
Why do people (not) share guilt with others?
Do people share their feelings of guilt with others and, if so, what are the reasons for doing this or not doing this? Even though the social sharing of negative emotional experiences, such as regret, has been extensively studied, not much is known about whether people share feelings of guilt and why. We report three studies exploring these questions. In Study 1, we re-analysed data about sharing guilt experiences posted on a social website called "Yahoo Answers", and found that people share intrapersonal as well as interpersonal guilt experiences with others online. Study 2 found that the main motivations of sharing guilt (compared with the sharing of regret) were "venting", "clarification and meaning", and "gaining advice". Study 3 found that people were more likely to share experiences of interpersonal guilt and more likely to keep experiences of intrapersonal guilt to themselves. Together, these studies contribute to a further understanding of the social sharing of the emotion guilt. </p
Toxic and Essential Trace Element Content of Commonly Administered Pediatric Oral Medications
OBJECTIVES: The aim of this study was to test the hypothesis that commonly administered pediatric oral medications are a significant source of toxic elements. The concentrations of 16 elements were determined in 14 frequently used pediatric oral medications.
METHODS: Samples were prepared for analysis by dilution or nitric acid microwave-assisted digestion and analyzed by inductively coupled plasma mass spectrometry. The intake of each element from administration for 1 week of the medication\u27s maximum recommended daily dose to 6-month-olds was calculated and compared to an exposure guideline for that element. Exposure guidelines used for adverse effects were minimal risk levels, oral reference dose, permissible or permitted daily exposure, provisional tolerable weekly intake, and tolerable upper intake concentrations. Exposure guidelines utilized for desired effect were adequate intake and recommended dietary allowance.
RESULTS: Intake of the maximum recommended daily dose by 6-month-olds for 1 week would not deliver more than the exposure guideline of any of the elements, with the exceptions of chromium in several medications and zinc in the pediatric electrolyte solution, if it was consumed for 1 week.
CONCLUSIONS: Consumed alone, these frequently administered pediatric oral medications would not deliver amounts of toxic elements that exceed established exposure guidelines for adverse effects, nor would most significantly contribute to adequate intake of essential elements
A culture of greed: Bubble formation in experimental asset markets with greedy and non-greedy traders
This study investigates the relationship between the motive of greed and various asset market indicators, such as trading activity and bubble formation (i.e., mispricing, overpricing, and price amplitude). We ran experimental asset markets that allowed us to measure individualsβ greed in order to create markets populated with greedy individuals and markets with non-greedy individuals. Regarding trading activity, we found that greedier individuals had higher trading activity on the individual level but not on the market level. On the market level, high-greed markets exhibited less frequent and smaller price bubbles than markets with less greedy traders. If our findings translate to actual markets, greed itself might not contribute to asset market bubbles
A Robust and Scalable Continuous Flow Process for Glycerol Carbonate
We report a robust continuous flow procedure for the synthesis of glycerol carbonate (2βGLC) from green reagents glycerol and dimethyl carbonate (DMC), mediated by an inexpensive polymerβsupported base catalyst using methanol as coβsolvent. High conversion and selectivity were obtained, while residence times were typically shorter than 10 minutes
Greedy bastards:Testing the relationship between wanting more and unethical behavior
Greed is often seen as immoral. Although the assumption that greed elicits unethical behavior is widespread, there is surprisingly little empirical research testing this relationship. We present a series of three studies investigating the association between greed and unethical behavior, using different methodologies and samples from the USA, The Netherlands, and Belgium. Study 1 (3 samples, total N = 3413) reveals that more greedy individuals find a variety of transgressions more acceptable and justifiable as well as indicate that they have more often engaged in a variety of transgressions compared to less greedy individuals. Study 2 (N = 172) replicated these findings in an incentivized behavioral laboratory study where participants decided to accept a bribe or not. Greedy people were more likely to take a bribe and also preferred higher bribes. Study 3 (N = 302) examined a potential process relating greed to unethical behavior. Greedy people were more likely to transgress because they found the positive outcomes associated with the transgression more desirable, and therefore displayed lower self-control. Implications for general theories of greed and morality are discussed
The vulnerabilities of computerized physician order entry systems: a qualitative study
Objective To test the vulnerabilities of a wide range of computerized physician order entry (CPOE) systems to different types of medication errors, and develop a more comprehensive qualitative understanding of how their design could be improved. Materials and Methods The authors reviewed a random sample of 63β040 medication error reports from the US Pharmacopeia (USP) MEDMARX reporting system where CPOE systems were considered a βcontributing factorβ to errors and flagged test scenarios that could be tested in current CPOE systems. Testers entered these orders in 13 commercial and homegrown CPOE systems across 16 different sites in the United States and Canada, using both usual practice and where-needed workarounds. Overarching themes relevant to interface design and usability/workflow issues were identified. Results CPOE systems often failed to detect and prevent important medication errors. Generation of electronic alert warnings varied widely between systems, and depended on a number of factors, including how the order information was entered. Alerts were often confusing, with unrelated warnings appearing on the same screen as those more relevant to the current erroneous entry. Dangerous drug-drug interaction warnings were displayed only after the order was placed rather than at the time of ordering. Testers illustrated various workarounds that allowed them to enter these erroneous orders. Discussion and Conclusion The authors found high variability in ordering approaches between different CPOE systems, with major deficiencies identified in some systems. It is important that developers reflect on these findings and build in safeguards to ensure safer prescribing for patients
Clinical impact of MDR1-expression in testicular germ cell cancer
Aim: The multidrug resistance protein 1 (MDR1, P-gp, p-170) is a membrane glycoprotein that acts as an energy-dependent drug efflux pump. In various malignancies its expression is associated with resistance to diverse cytostatic drugs, and therefore predicts resistance to systemic treatment. The aim of this study was to investigate the prognostic value of MDR1 expression in primary tumor tissue to predict necrosis or viable cancer in residual tumor masses after systemic chemotherapy for advanced testicular germ cell cancer. Materials and Methods: Out of 77 patients, histopathological characteristics of primary testicular cancer specimens and retroperitoneal lymph node dissection (RPLND) samples following chemotherapy were available from 72 and all 77 patients, respectively. Moreover, MDR1 expression was determined by immunohistochemistry in 47 primary tumors and corresponding 73 RPLND sections. Results: After chemotherapy and subsequent RPLND, the examination of residual tumor masses revealed that mature teratoma and active viable tumor were predominantly found in patients with non-seminoma (NSGCT; p = 0.048), especially in those with containing mature teratoma (p = 0.001). Moreover, using univariate analysis the expression of MDR1 in the primary testicular tumor predicted viable tumor/teratoma residues in RPLND sections (p = 0.003). However, in multivariate analysis including the tumorsβ histological subtype, MDR1 expression alone failed to reach statistical significance as an independent prognostic marker for residual vital tumor (p β₯ 0.16). Conclusions: With the limited number of patients given, the correlation between MDR1 expression in primary testis cancer and active residual retroperitoneal disease after chemotherapy failed to reach statistical significance as in independent marker. Therefore, up to now routine MDR1 staining of testicular germ cell cancer samples should not be performed in clinical practice. However, as there was a clear trend, a larger number of patients suffering from metastatic non-seminomas should be studied, as MDR1 expression might have significant prognostic value in this particular subgroup of patients.ΠΠ΅Π»ΠΎΠΊ 1 ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π»Π΅ΠΊΠ°ΡΡΡΠ² Π΅Π½Π½ΠΎΠΉ ΡΡΡΠΎΠΉΡΠΈΠ² ΠΎΡΡΠΈ (MDR1, P-gp, p-170) β ΡΡΠΎ ΠΌΠ΅ΠΌΠ±ΡΠ°Π½Π½ΡΠΉ Π³Π»ΠΈΠΊΠΎΠΏΡΠΎΡΠ΅ΠΈΠ½, ΡΡΠ½ΠΊΡΠΈΠΎΠ½ΠΈΡΡΡΡΠΈΠΉ ΠΊΠ°ΠΊ ΡΠ½Π΅ΡΠ³ΠΎΠ·Π°Π²ΠΈΡΠΈΠΌΡΠΉ Π½Π°ΡΠΎΡ. ΠΡΠΈ ΡΠ°Π·Π» ΠΈΡΠ½ΡΡ
ΡΠΎ ΡΠΌΠ°Ρ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ Π΅Π³ΠΎ ΡΠΊΡΠΏΡ Π΅ ΡΡΠΈΡ ΡΠ²ΡΠ·Π°Π½Π° Ρ ΡΡΡΠΎΠΉΡΠΈΠ² ΠΎ ΡΡΡΡ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΊ
ΡΠ°Π·Π»ΠΈΡΠ½ΡΠΌ ΡΠΈΡΠΎΡΡΠ°ΡΠΈΠΊΠ°ΠΌ, ΡΡΠΎ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΎ Π΄Π»Ρ Π²ΡΠ±ΠΎΡΠ° ΡΠΈΠΏΠ° ΡΠ΅ΡΠ°ΠΏΠΈΠΈ. Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ β ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈ-
ΡΠ΅ΡΠΊΠΎΠΉ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΠΈ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ MDR1 Π² ΡΠΊΠ°Π½ΠΈ ΠΏΠ΅ ΡΠ²ΠΈΡΠ½ΠΎΠΉ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Π²ΠΎΠ·ΠΌΠΎ ΠΆΠ½ΠΎΡΡΠΈ ΡΠ°Π· Π²ΠΈΡΠΈΡ Π½Π΅ΠΊΡΠΎΠ·Π° ΠΈΠ»ΠΈ ΡΠΎΡ
ΡΠ°Π½ Π΅ Π½ΠΈΡ
ΠΆΠΈΠ²ΡΡ
ΠΊΠ»Π΅ΡΠΎΠΊ Π² ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΏΠΎΡΠ»Π΅ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠΉ Ρ
ΠΈΠΌΠΈΠΎΡΠ΅ΡΠ°ΠΏΠΈΠΈ Π½Π° ΠΏΠΎΠ·Π΄Π½ΠΈΡ
ΡΡΠ°Π΄ΠΈΡΡ
Π³Π΅ΡΠΌΠΈΠ½Π°ΡΠΈΠ²Π½ΡΡ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ ΡΠΈΡΠΊΠ°. ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ: ΠΏΡΠΎ Π°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎ Π²Π°Π½Ρ Π³ΠΈΡΡΠΎ ΠΏΠ°ΡΠΎΠ»ΠΎ Π³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Ρ
Π°ΡΠ°ΠΊΡ Π΅ ΡΠΈΡΡΠΈΠΊΠΈ ΠΏΠ΅ ΡΠ²ΠΈΡΠ½ΠΎ ΠΉ ΡΠ΅ ΡΡΠΈΠΊΡΠ»ΡΡΠ½ΠΎΠΉ
ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΈ ΠΎΠ±ΡΠ°Π·ΡΠΎΠ², ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ
ΠΏΡΠΈ ΠΈΡΡΠ΅ΡΠ΅Π½ΠΈΠΈ ΡΠ΅ΡΡΠΎΠΏΠ΅ΡΠΈΡΠΎΠ½Π΅Π°Π»ΡΠ½ΡΡ
Π»ΠΈΠΌΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ·Π»ΠΎΠ² (RPLND) ΠΏΠΎΡΠ»Π΅ Ρ
ΠΈΠΌΠΈ ΠΎΡΠ΅ΡΠ°ΠΏΠΈΠΈ
72 ΠΈ 77 Π±ΠΎΠ» ΡΠ½ΡΡ
ΡΠΎΠΎΡΠ²Π΅ ΡΡΡΠ²Π΅Π½Π½ΠΎ. ΠΠΊΡΠΏΡ Π΅ΡΡΠΈΡ MDR1 ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈ ΠΈΠΌΠΌΡΠ½ ΠΎΠ³ΠΈΡΡ ΠΎΡ
ΠΈΠΌΠΈΡ Π΅ΡΠΊΠΈΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ Π² 47 ΠΎΠ±ΡΠ°Π·ΡΠ°Ρ
ΠΏΠ΅ΡΠ²ΠΈΡΠ½ ΠΎΠΉ
ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΈ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΡ
73 ΡΡ RPLND. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: ΠΏΠΎΡΠ»Π΅ Ρ
ΠΈΠΌΠΈ ΠΎΡΠ΅ΡΠ°ΠΏΠΈΠΈ ΠΈ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΉ RPLNDΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈ Π΅ ΠΎΡΡΠ°-
ΡΠΎΡΠ½ΡΡ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΡΠΊΠ°Π½Π΅ΠΉ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΎ, ΡΡΠΎΠ·ΡΠ΅Π»Π°Ρ ΡΠ΅ΡΠ°ΡΠΎΠΌΠ° ΠΈ ΠΆΠΈΠ·Π½Π΅ΡΠΏΠΎΡΠΎΠ±Π½ΡΠ΅ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΠ΅ ΠΊΠ»Π΅ΡΠΊΠΈ Π²ΡΡΠ² Π»ΡΡΡ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎ
Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
, Ρ ΠΊΠΎΡΠΎΡΡΡ
Π½Π΅ Π±ΡΠ»Π° ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½Π° ΡΠ΅ΠΌΠΈΠ½ΠΎΠΌΠ° (NSGCT; p = 0,048), ΠΎΡΠΎΠ±Π΅Π½Π½ΠΎ Ρ ΡΠ°ΠΊ ΠΎΠ²ΡΡ
, Ρ ΠΊΠΎΡΠΎΡΡΡ
Π±ΡΠ»Π° ΡΠ΅ΡΠ°ΡΠΎΠΌΠ° (p =
0,001). ΠΠΎΠ»Π΅Π΅ ΡΠΎΠ³ΠΎ, Π΄ Π°Π½Π½ΡΠ΅ ΠΎΠ΄Π½ΠΎ ΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ, ΡΡΠΎ ΡΠΊΡΠΏΡ Π΅ ΡΡΠΈΡ MDR1 Π² ΡΠΊΠ°Π½ΠΈ ΠΏΠ΅ ΡΠ²ΠΈΡΠ½ΠΎ ΠΉ ΡΠ΅ ΡΡΠΈΠΊΡ Π»ΡΡΠ½ΠΎΠΉ ΠΎΠΏΡ-
Ρ
ΠΎΠ»ΠΈ ΠΌΠΎΠΆΠ΅Ρ ΡΠ»ΡΠΆΠΈΡΡ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡ Π΅ΡΠΊΠΈΠΌ ΡΠ°ΠΊΡ ΠΎΡΠΎΠΌ ΡΠΎΡ
ΡΠ°Π½ Π΅Π½ΠΈΡ ΠΆΠΈΠ²ΡΡ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΠΊ ΡΡΠ΅Π·Π°Ρ
RPLND (p = 0,003). Π Π½Π°ΠΊ ΠΎ
ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΌΡΠ»ΡΡΠΈΡΠ°ΠΊΡΠΎΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π°, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Ρ ΡΡΠ΅ΡΠΎΠΌ Π³ΠΈΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΏΠΎΠ΄ΡΠΈΠΏΠ° ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ, ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΎ, ΡΡΠΎ ΡΠΊΡΠΏΡ Π΅ ΡΡΠΈΡ
MDR1 Π½Π΅ ΠΈΠΌΠ΅Π΅Ρ ΡΠ°ΠΌΠΎΡΡΠΎΡΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π·Π½Π°ΡΠΈΠΌΠΎΡΡΠΈ Π΄Π»Ρ Π²ΡΡΠ²Π»Π΅Π½ΠΈΡ ΠΆΠΈΠ²ΡΡ
ΠΎΡΡΠ°ΡΠΎΡΠ½ΡΡ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΠΊ (p
0,16). ΠΡΠ²ΠΎΠ΄Ρ: Π²Π²ΠΈΠ΄Ρ Π½Π΅Π±ΠΎΠ»ΡΡΠΎ ΠΉΠ²ΡΠ±ΠΎΡΠΊΠΈΠ±ΠΎΠ»ΡΠ½ΡΡ
Π½Π΅ Π²ΡΡΠ² Π»Π΅Π½ΠΎ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π·Π½Π°ΡΠΈΠΌΠΎΠΉΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΈ ΠΌΠ΅ΠΆΠ΄Ρ ΡΠΊΡΠΏΡ Π΅ΡΡΠΈΠ΅ΠΉ MDR1
Π² ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΠΎΠΉ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΡΠΈΡΠΊΠ° ΠΈ Π½Π°Π»ΠΈΡΠΈΠ΅ΠΌ Π°ΠΊΡΠΈΠ²Π½ΡΡ
ΡΠ΅Π·ΠΈΠ΄ΡΠ°Π»ΡΠ½ΡΡ
ΠΎΡΠ°Π³ΠΎΠ² ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΡ Π² ΡΠ΅ΡΡΠΎΠΏΠ΅ΡΠΈΡΠΎΠ½Π΅Π°Π»ΡΠ½ΠΎΠΌ ΠΏΡΠΎΡΡΡΠ°Π½ΡΡΠ²Π΅. Π Ρ ΠΎ
ΠΆΠ΅ Π²ΡΠ΅ΠΌΡ, ΡΡΠΈΡΡΠ²Π°Ρ Π²ΡΡΠ²Π»Π΅Π½Π½ΡΡ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡ, ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΡ MDR1, Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠ³Π½ΠΎΡΡΠΈΡ Π΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠ°ΡΠΊ Π΅ΡΠ°, ΠΈΠΌΠ΅Π΅Ρ
ΡΠΌΡΡΠ» ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΡ ΠΈΠΌΠ΅Π½Π½ΠΎ Ρ Π±ΠΎΠ»ΡΠ½ΡΡ
Ρ ΠΌΠ΅ΡΠ°ΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΎΠΏΡΡ
ΠΎΠ»ΡΠΌΠΈ, Π½Π΅ ΡΠ²Π»ΡΡΡΠΈΠΌΠΈΡΡ ΡΠ΅ΠΌΠΈΠ½ΠΎΠΌΠΎΠΉ
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