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"Lupus nephritis (LN) is involvement of the kidney in patient with systemic lupus erythematosus (SLE) and one of the most common target organ in SLE. The diagnosis of LN will significantly impact the clinical outcome and therapy of the patient. Therapy regiment of LN is divided into two stages, induction and maintenance treatment. The main objective of the induction therapy is to achieve complete or partial remission as soon as possible since it is correlated with better prognosis and fewer relapse incidence. In the maintenance stage, the main aim of the therapy is to maintain the remission status and avoid future relapse. It is also important to evaluate the effectiveness of the therapy as it will affect the duration and the regiment therapy being used. Corticosteroid, cyclophosphamide, mycophenolate mofetil, azathrioprine, cyclosporine and tacrolimus are example of drugs used in LN therapy. Currently, studies are being conducted to evaluate and develop targeted drug therapy to further add treatment options for LN.

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efritis lupus (NL) adalah keterlibatan organ ginjal pada pasien lupus eritematosus sistemik (LES) dan merupakan salah satu keterlibatan organ yang paling sering ditemukan. Ditemukannya NL pada pasien LES akan berdampak besar baik secara prognosis dari pasien maupun dalam pengobatan itu sendiri. Pengobatan NL dibagi menjadi dua tahap, induksi dan rumatan. Target dari pengobatan tahap induksi adalah untuk secepatnya mencapai remisi, baik parsial ataupun komplit, karena akan memberikan prognosis yang lebih baik dan kejadian relapse yang lebih rendah. Pada tahap rumatan, target yang ingin dicapai adalah untuk mempertahankan status remisi dan mencegah terjadinya relapse. Evaluasi keberhasilan dari masing-masing tahap juga sangat penting karena akan berpengaruh pada kelanjutan pengobatan. Kortikosteroid, siklofosfamid, mikofenolat mofetil, azatioprin, siklosporin dan takrolimus adalah obat-obat yang biasa dipakai dalam pengobatan NL. Berbagai target pengobatan baru juga terus berkembang guna memberikan pilihan yang lebih luas dalam menangani kejadian NL."

"Pasien kanker kolorektal (KKR) dengan stadium yang sama dapat mengalami hasil luaran berbeda, yang disebabkan berbagai faktor antara lain faktor imunitas pasien (sel T-CD3 dan CD8) dan lingkungan mikrotumor (tumor budding). Tujuan dari penelitian ini adalah menganalisis hubungan densitas sel T-CD3 dan CD8, status MMR, TB dengan gambaran klinikopatologi (usia, jenis kelamin, diferensiasi, lokasi, kedalaman invasi tumor, penyebaran kelenjar getah bening), metastasis dan kesintasan KKR. Penelitian observasional, kohort, retrospektif selama 36 bulan, menggunakan 68 blok parafin kasus KKR yang menjalani pengangkatan tumor sebagai pengobatan pertama. Pemeriksaan imunohistokimia digunakan untuk menentukan densitas sel T-CD3, CD8, MLH1, MSH6 dan TB. Pasien laki-laki lebih banyak dari perempuan, rerata usia 56,2 tahun. TB dengan kedalaman invasi tumor (pT), penyebaran kelenjar getah bening dan metastasis ditemukan hubungan bermakna. Selain itu ditemukan hubungan bermakna usia dengan status MMR, metastasis dengan TB, kesintasan dengan pT dan kesintasan dengan metastasis. Densitas sel T-CD8 dan metastasis dapat digunakan sebagai faktor prognostik kesintasan pasien KKR. Densitas sel T-CD8 tinggi dan metastasis organ dapat dipakai sebagai faktor prognosis kesintasan pada pasien KKR. TB tinggi sesuai dengan kedalaman invasi tumor, penyebaran kelenjar getah bening dan metastasis organ. Status MMR tidak berhubungan dengan gambaran klinikopatologi tapi dapat digunakan untuk menentukan jenis pengobatan.

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Colorectal cancer (CRC) patients with the same stage produce different outcomes, which are caused by various factors including patient immunity factors (CD3 and CD8-T cells) and the microenvironment tumor (tumor budding). The purpose of this study was to analyze the relationship between CD3 and T-CD8 cell density, MMR status, TB with clinicopathological features, metastasis and CRC survival. This study is observational, cohort, 36 months retrospective on 68 Formalin-Fixed Paraffin-Embedded (FFPE) of CRC, who underwent tumor removal as the first treatment. Immunohistochemical examination was used to determine T-CD3 cells, CD8, MLH1, MSH6 and TB. There were more male patients than female patients, the average age was 56.2 years.TB with the depth of tumor invasion (pT), lymph node and metastasis were significantly related. There was a significant relationship between age and MMR status, metastasis with TB, survival with pT and survival with metastasis. T-CD8 cell density and metastasis used as prognostic factors for survival of CRC patients. High CD8 T-cell density and metastasis used as prognostic factors for survival in CRC patients. High TB in accordance with the depth of tumor invasion, lymph node and metastasis. MMR status is not related to clinicopathological features but used to determine the appropriate treatment."

"This volume presents information on stem cells and cancer stem cells, therapeutic applications in disease and tissue/organ injury. Methodologies of regenerative medicine and tissue engineering are major components of this volume. Specific stem cells discussed are, human embryonic stem cells, hematopoietic stem cells, cord blood stem cells, human pluripotent stem cells, gliosarcoma stem cells, induced pluripotent stem cells, intestinal stem cells, human thyroid cancer stem cells, tumor stem cells, menstrual stem-like cells, neural stem cells, breast cancer stem cells, allogeneic mesenchymal stem cells, fetal membrane-derived mesemchynmal stem cells, and omental stem cells. The method for isolating bone marrow stromal cells is explained. Method for generating marmoset-induced pluripotent stem cells, using transcription factors, is also explained. Use of stem cell lines in therapeutic applications is discussed. Programming of stem cells is described. Methods for transplantation of stem cells are presented. Use of various types of stem cells for conditions such as stroke, ischemia, heart diseases, Alzhemier’s disease, and neurogenerative diseases in general, is explained. For example, generation of human cardiac muscle cells from adipose-derived stem cells is included. Another example is repairing bone defects using mesenchymal stem cells and mesenchymal-derived endothelial cells. Differentiation of new neurons from neural stem cells is described. Method for repairing retina condition using human embryonic stem cells is explained; these cells can induce neural differentiation. Treatment of graft-versus-host disease resulting from hematopoietic stem cell transplantation is elaborated."

"PurposeThe association between the preoperative absolute neutrophil count (NC), lymphocyte count (LC), and monocyte count (MC) in the peripheral blood and the prognosis of gastric cancer (GC) patients has not been investigated widely.MethodsWe enrolled 445 patients who underwent surgery for GC between January, 2005 and April, 2013 to analyze the correlations among NC, LC, and MC and their prognoses.ResultsBased on cut-off values calculated by ROC analysis, patients were sub grouped as having: NC ≥ 4477 (NCHigh), NC < 4477 (NCLow); and as LC ≥ 1447 (LCHigh), LC < 1447 (LCLow); and as MC ≥ 658,5 (MCHigh), MC < 658,5 (MCLow). Each group was assigned as follows; NCHigh group = 1, NCLow group = 0, LCHigh group = 0, LCLow group = 1, MCHigh group = 1, MCLow group = 0, and the sum of each score was defined as the lymphocyte-monocyte-neutrophil score (LMN score). The overall 5-year survival rates were 89%, 74%, 57,8%, and 53,3% for LMN scores of 0, 1, 2, and 3, respectively (P = 0,0004). Multivariate analysis indicated that the LMN score was an independent prognostic indicator.ConclusionsThe combination of preoperative NC, LC, and MC appears to be a useful indicator of GC prognosis."

"Latar Belakang: Kanker serviks adalah keganasan ginekologi terbanyak kedua pada perempuan di seluruh dunia dengan angka kematian yang tinggi. Stadium IIIB kanker serviks didefinisikan sebagai perluasan tumor yang mengenai dinding panggul atau adanya hidronefrosis. Jika disertai dengan gangguan ginjal, angka morbiditas dan mortalitas pasien akan meningkat. Penelitian ini bertujuan untuk mengkaji perbedaan data patologi, respon terapi, masa rawat, dan angka kesintasan satu tahun pada pasien kanker serviks stadium IIIB dengan dan tanpa gangguan ginjal. Metode: Dengan menggunakan metode potong lintang dilakukan pengambilan data 941 sampel pasien kanker serviks stadium IIIB di RSCM Jakarta antara bulan Juli 2010 - Juli 2015. Hasil: Hasil penelitian menunjukkan terdapat perbedaan signifikan jumlah pasien ditinjau dari keterlibatan dinding panggul, keterlibatan KGB, derajat dan simetrisitas hidronefrosis, rerata kadar ureum, kreatinin, dan kalium serum pada pasien kanker serviks dengan dan tanpa gangguan ginjal (p<0.001). Juga ditemukan perbedaan bermakna jumlah pasien yang menjalani terapi diversi urin , dialisis, dan kemoterapi. Untuk analisis kesintasan, didapatkan hazard ratio 0.307 (IK95% 0,160-0,589). Kesimpulan: Dengan gambaran data tersebut, perlu diusulkan suatu entitas klasifikasi baru untuk kanker serviks stadium IIIB dengan gangguan ginjal (IIIB plus), mengingat kasus ini membutuhkan penanganan yang lebih kompleks dan holistik dengan melibatkan banyak keahlian (penyakit dalam, urologi, ginjal hipertensi, gizi klinik dan paliatif) serta prognosis yang berbeda bermakna secara statistik

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Background: Cervical cancer is the second most common gynecological cancer in women globally. Stage IIIB cervical cancer is defined as a local extension of tumor that affects the pelvic wall or hydronephrosis or kidney disease. If accompanied by kidney disease, the complication will increase thereby increasing patient's morbidity and mortality. The aim of this study is to know whether there are differences in the clinical data, therapy, duration of hospital, and one-year survival rate in cervical cancer patient with and without kidney disease.

Methods: This research uses cross-sectional method with samples of stage IIIB cervical cancer patients in Cipto Mangunkusumo between July 2010 and July 2015.

Results: The results showed significant difference in the number of patients with pelvic wall involvement, lymph node involvement, degree and symmetry of hydronephrosis, the serum urea, creatinine, and potassium level between cervical cancer patients with and without kidney disease (p <0.001). There are also significant differences in the number of patients undergoing urinary diversion therapy, dialysis and chemotherapy. For survival analysis, the hazard ratio obtained is 0.307 (IK95% 0.160 - 0.589).

Conclusion: With the results obtained, we suggest new entitiy for cervical cancer stage IIIB with kidney disease ( IIIB plus), according to there is an obligation of more complex involvement of specialist (internist, urologist, renal hypertension expert, clinical nutrition and palliative expert) and statistically the prognosis is different"

"Kanker payudara adalah kanker yang biasa terjadi pada wanita dan merupakan jenis kanker yang cukup agresif. Cukup sulit bagi dokter untuk dapat mengobati dan memprediksi harapan hidup kasus pada kanker payudara invasif karena kanker jenis tersebut cukup kompleks. Dengan menggunakan model prediksi pembelajaran mesin yang lebih akurat, dapat membantu dokter dalam mengambil keputusan penanganan dan terapi yang tepat untuk pasien. Untuk dapat memprediksi prognosis kanker payudara tersebut, pada penelitian ini diusulkan model stacked based ensemble berbasis deep learning dan menggunakan multi-modal data. Penulis melakukan pengembangan model dengan menggunakan residual connection dan voting classifier. Penggunaan residual connection dapat membantu mencegah terjadinya informasi hilang saat pergantian layer. Sedangkan voting classifier dapat membantu mengurangi error dari setiap algoritma model klasifikasi. Evaluasi performa dari prediksi akhir model yang digunakan adalah accuracy. Model yang diusulkan dengan residual connection memiliki nilai accuracy sebesar 91.7%, yaitu lebih tinggi 1,5% dari model sebelumnya. Ketika  model dengan residual connection ditambahkan dengan voting classifier, maka nilai accuracy yang dihasilkan sebesar 95.9%, yaitu lebih tinggi 5.7% dibandingkan dengan model acuan.

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Breast cancer is a cancer that usually occurs in women and is a type of cancer that is quite aggressive. It is quite difficult for doctors to be able to treat and predict case survival in invasive breast cancer because this type of cancer is quite complex. By using a more accurate machine learning prediction model, it can assist doctors in making the right treatment and therapy decisions for patients. To be able to predict the prognosis of breast cancer, this study proposes a stacked ensemble based model based on deep learning and using multi-modal data. The author develops the model by using residual connection and voting classifier. The use of residual connections can help prevent information loss when changing layers. While voting classifier can help reduce the error of each classification model algorithm. The performance evaluation of the final prediction of the model used is accuracy. The proposed model with a residual connection has an accuracy value of 91.7%, which is 1.5% higher than the previous model. When a model with a residual connection is added with a voting classifier, the resulting accuracy value is 95.9%, which is 5.7% higher than the reference model."