1 Pengaruh Mengkonsumsi Rebusan Daun Sirsak Terhadap Penurunan Nyeri Pada Penderita Gout Artritis Di Wilayah Kerja Puskesmas Pineleng

Gout artritis merupakan penyakit yang ditandai dengan nyeri yang terjadi berulang-ulang yang disebabkan adanya endapan kristal monosodium urat yang tertumpuk di dalam sendi sebagai akibat tingginya kadar asam urat di dalam darah. Mengkonsumsi rebusan daun sirsak (Anonna muricata) adalah salah satu jenis terapi nonfamakologi yang bertujuan untuk menurunkan tingkat nyeri pada penderita gout artritis karena senyawa yang terkandung dalam daun sirsak berfungsi sebagai analgetik yang mempu mengurangi nyeri gout.Tujuan penelitan ini adalah untuk menganalisis pengaruh mengkonsumsi rebusan daun sirsak terhadap penurunan nyeri pada penderita gout artritis di wilayah kerja Puskesmas Pineleng.Sampel diambil dengan menggunakan total sampling yaitu 34 orang yang memenuhi kriteria inklusi.Desain penelitian yang digunakan adalah Time Series Design dan data yang dikumpulkan dari responden menggunakan lembar observasi.Hasil penelitian uji Wilcoxon sign rank test pada hasil akhir didapatkan nilai p = 0,004 < α = 0,005 sehingga dapat diambil Kesimpulan bahwa hipotesis penelitian diterima, hal ini menunjukan bahwa ada pengaruh mengkonsumsi rebusan daun sirsak terhadap penurunan nyeri pada penderita gout artritis di wilayah kerja Puskesmas Pineleng.Saran untuk penelitian selanjutnya dapat menggunakan populasi yang lebih besar untuk hasil yang lebih akurat serta dapat mengembangkan penelitian tentang pengaruh mengkonsumsi rebusan daun sirsak terhadap variabel yang lain seperti penurunan tekanan darah pada penderita hipertensi

Implementasi Program Wirausaha Baru Oleh Dinas Tenaga Kerja Dan Transmigrasi Dalam Mendukung Gerdu Kempling Kota Semarang Tahun 2014

The Government of Semarang through Local Regulation Number 4 of 2008 about poverty reduction in Semarang City which is an acceleration in poverty reduction efforts. The strategy called Gerdu Kempling (Integrated Health, Economy, Education, Infrastructure, and Environment ) and one of the program that is New Entrepreneur Program by Dinas Tenaga Kerja dan Transmigrasi Kota Semarang. This research was meant to find out how the implementation of New Entrepreneur Program by Dinas Tenaga Kerja Dan Transmigrasi that supports Gerdu Kempling Kota Semarang in 2014 and knowing the influence factors of this implementation. New Entrepreneur Program has been part of Gerdu Kempling starting in 2011. There are three locations in this research: Village of Bulusan, Ngadirgo and Padangsari. This research using qualitative descriptive research methods. The subject in this study consisted of eight (8) informants. The results showed that the implementation of New Entrepreneur Program are still less effective that is seen from the precision implementation aspects. The factors that influence the implementation such as the goals and basic of policy, resource policy, communication and implementation activities, the implementing agency characteristics, external conditions as well as the disposition of the implementor are still less optimal too. Based on these conclusions, the researcher recommend to the implementation agency and target of this program need high commitment and take maximal advantages for sustainable in order to achieve the purpose of this program

A Stochastic Model Correctly Predicts Changes in Budding Yeast Cell Cycle Dynamics upon Periodic Expression of <i>CLN2</i>

<div><p>In this study, we focus on a recent stochastic budding yeast cell cycle model. First, we estimate the model parameters using extensive data sets: phenotypes of 110 genetic strains, single cell statistics of wild type and <i>cln3</i> strains. Optimization of stochastic model parameters is achieved by an automated algorithm we recently used for a deterministic cell cycle model. Next, in order to test the predictive ability of the stochastic model, we focus on a recent experimental study in which forced periodic expression of <i>CLN2</i> cyclin (driven by <i>MET3</i> promoter in <i>cln3</i> background) has been used to synchronize budding yeast cell colonies. We demonstrate that the model correctly predicts the experimentally observed synchronization levels and cell cycle statistics of mother and daughter cells under various experimental conditions (numerical data that is not enforced in parameter optimization), in addition to correctly predicting the qualitative changes in size control due to forced <i>CLN2</i> expression. Our model also generates a novel prediction: under frequent <i>CLN2</i> expression pulses, G1 phase duration is bimodal among small-born cells. These cells originate from daughters with extended budded periods due to size control during the budded period. This novel prediction and the experimental trends captured by the model illustrate the interplay between cell cycle dynamics, synchronization of cell colonies, and size control in budding yeast.</p></div

Synchronization levels with different forcing periods.

<p> is the fraction of time points (between 300 min and 700 min) at which more than 95% or less than 5% of the cells are budded during 700 min simulations. The simulation statistics (mean standard deviation) of are computed from 15 independent realizations per forcing period. In each realization, a budding index trajectory is generated from a single pedigree of cells. Each pedigree starts from a single cell and the number of cells within the pedigree increases exponentially due to cell division. Values that are in parentheses are from the pedigrees that are initiated by single mother cells, whereas the remaining values are from the pedigrees that start with daughter cells. Results are consistent with these different initial condition choices.</p

Changes in G1 and S/G2/M size control upon forced <i>CLN2</i> expression with different forcing periods.

<p> and (both defined in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096726#s2" target="_blank">Methods</a> section) quantify the changes in the size control strength in G1 and S/G2/M phases, respectively for mother (M) or daughter (D) cells. For small cells at budding (in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096726#pone-0096726-g009" target="_blank">Figures 9B, 9C, and 9D</a>), . Here, the cell area at budding is denoted by . The percentage of small cells at budding increases as the pulses become more frequent. Changes in size control are computed from the aggregation of eight independently generated pedigrees per forcing period.</p

Fractions of locked daughters and mothers.

<p>Forced <i>CLN2</i> expression with six forcing periods: experimental <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096726#pone.0096726-Charvin1" target="_blank">[7]</a> and simulation values for daughters in (A) and mothers in (B). Black vertical lines represent the natural (<i>cln3</i>, no forced <i>CLN2</i> expression) mother and daughter cycle times. The range of each locked fraction in the simulations (mean standard deviation) is depicted by the blue error bars, whereas the red circles correspond to experimental values. Each range from the simulations is computed from 15 independent realizations. Each realization contains eight independently generated pedigrees of cells generated over the course of 700 min starting from a single daughter or mother cell.</p

Analysis of the trajectories shown in Figure 7.

<p>Shown is the number of budding events that show lack of synchrony with the pulse for mother (M) or daughter (D) cells in 1000 min simulations. The number of observations until 700 min is shown in parentheses. Pulse skipping happens when the cell does not bud between two subsequent pulses, whereas observing multiple budding events between subsequent pulses is a consequence of the natural cycle time (with no forced <i>CLN2</i> expression) being significantly shorter than the forcing period. The total number of cycles without forced <i>CLN2</i> expression (<i>cln3</i>) is given in the last two rows for daughters and mothers, respectively. The numbers of pulse skipping events, multiple budding events, and total number of cycles are computed from a single mother or daughter trajectory per forcing period.</p

Characterization of size control in the G1 phase.

<p>Raw data from the <i>cln3</i> simulations (A) and the simulations with 90 min (B), 78 min (C), and 69 min (D) periods of forced <i>CLN2</i> expression. Cell area at birth is denoted by , whereas is the rate of exponential cell growth and is the G1 duration. “D” and “M” stand for daughters and mothers, respectively. Simulation data is collected from eight independently generated pedigrees per forcing period.</p

Simulated return maps for successive mother and daughter cells.

<p>Forced <i>CLN2</i> expression periods are 90 min in (A) and (D), 78 min in (B) and (E) and 69 min in (C) and (F). “D” and “M” stand for daughters and mothers, respectively. As the forcing period approaches the mother/daughter natural cycle time (71/94 min) the maximum data density on the mother/daughter return map increases. Colors represent the fraction of data points in each map region as depicted in the color map on the right. Only the bright colors of this map are used in the return maps except for the map regions with very low data density. Lines are depicted in yellow. Each return map is made using the data collected from eight independently generated pedigrees.</p

Characterization of size control in the S/G2/M phase.

<p>Raw data from the <i>cln3</i> simulations (A) and the simulations with 90 min (B), 78 min (C), and 69 min (D) periods of forced <i>CLN2</i> expression. Cell area at budding is denoted by , whereas is the rate of exponential cell growth and is the budded period duration. “D” and “M” stand for daughters and mothers, respectively. Simulation data is collected from eight independently generated pedigrees per forcing period.</p