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Abstrak :
Anticarbohydrate antibodies provides a cohesive overview of current knowledge on the immunological recognition of carbohydrates by the adaptive immune system. The text provides fundamental insight needed for advancing clinically relevant diagnostics and therapeutic applications.

Abstrak :
Pendahuluan dan tujuan: Kanker penis merupakan keganasan yang jarang terjadi dan berpotensi mematikan dengan insidensi 0,6-2,1 per 100.000. Karsinoma sel skuamosa (SqCC) adalah keganasan penis yang paling sering ditemukan. PD-L1 adalah penanda tumor yang ikut menstimulasi reseptor PD-1 untuk menekan imunitas antitumor yang dimediasi oleh sel T. Metode: Penelitian ini merupakan studi kohort retrospektif dengan metode pengambilan sampel total. Slide yang diambil dari biopsi tujuh puluh enam pasien pria dari Rumah Sakit Haji Adam Malik yang didiagnosis dengan karsinoma sel skuamosa penis yang telah menjalani biopsi penis diperiksa ulang untuk penelitian ini, dan kadar PD-L1 diukur. Metode statistik digunakan untuk menilai hubungan antara kadar PD-L1 dan stadium SqCC. Hasil: Sebanyak 76 pasien pria menjadi subjek penelitian ini. PD-L1 positif diidentifikasi pada 25 pasien dengan intensitas +1 pada 10 pasien (13,2%), +2 pada 7 pasien (9,2) dan intensitas +3 pada 8 pasien (10,5%). Terdapat 36 pasien (47,4%) yang didiagnosis dengan stadium T3 SqCC, 35 pasien (46,1%) dengan stadium N2 SqCC, dan 10 pasien (13,2%) dengan stadium M1 SqCC. Terdapat korelasi yang signifikan antara ekspresi PD-L1 dan metastasis (p=0,022). Namun, tidak ada korelasi yang signifikan antara ekspresi PD-L1 dan tumor stadium N (p=0,167). Kesimpulan: PD-L1 diekspresikan secara tinggi pada SqCC penis stadium lanjut (32,9%), yang dikaitkan dengan fitur klinikopatologis berisiko tinggi dan hasil klinis yang buruk. Temuan ini menunjukkan potensi penggunaan imunoterapi dalam pengobatan SqCC penis stadium lanjut. ......Introduction: Penile cancer is a rare malignancy and potentially lethal disease with an incidence of 0,6-2,1 per 100.000. Squamous cell carcinoma (SqCC) is the most commonly found penile malignancy. PD-L1 is a tumor marker that co-stimulates the receptor PD-1 to suppress T-cell- mediated antitumor immunity. Methods: This study is a retrospective cohort study with a total sampling method. The slides taken from the biopsies of seventy-six male patients from Haji Adam Malik Hospital diagnosed with penile squamous cell carcinoma who have already undergone penile biopsy were re-examined for this study, and PD-L1 levels were measured accordingly. Statistical methods were used to assess the association between PD-L1 levels and with SqCC stage. Results: A total of 76 male patients are the subjects of this study. PD-L1 positivity is identified in 25 patients with +1 intensity in 10 patients (13,2%), +2 in 7 patients (9,2) and +3 intensity in 8 patients (10,5%). There are 36 patients (47,4%) diagnosed with stage T3 SqCC, 35 patients (46,1%) with stage N2 SqCC, and 10 patients (13,2%) with stage M1 SqCC. There is significant correlation between PD-L1 expression and metastasis (p=0,022). However, there is no significant correlation between PD-L1 expression and stage N tumor (p=0,167). Conclusion: PD-L1 highly expressed in advanced stage penile SqCC (32.9%), which is associated with the high-risk clinicopathologic features and poor clinical outcomes. These findings showed a potential usage of immunotherapy in advanced penile SqCC treatment.

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PURPOSE: House dust mites (HDM) are major allergens that cause allergic rhinitis (AR). Allergen-specific subcutaneous immunotherapy (SCIT) has been shown to be clinically beneficial in many clinical trials. Such trials, however, are not reflective of all patient populations. The aim of this study was to describe the efficacy and safety of SCIT in routine clinical practice in Korean adults with AR sensitized to HDM. METHODS: We reviewed medical records of 304 patients with AR treated at an allergy clinic of a tertiary hospital using SCIT with aluminum hydroxide-adsorbed allergen extract targeting HDM alone or with pollens for at least 1 year from 2000 to 2012. Patients with asthma were excluded. Rates of remission, defined as no further requirement of maintenance medication, over time were determined by means of life tables and extension of survival analysis. Specific immunoglobulin E (IgE) levels to HDM were categorized into 6 classes. RESULTS: The mean time until achieving remission was 4.9±0.1 years, and the cumulative incidence of remission from AR was 76.6%. Severe AR (odds ratio [OR], 0.40; 95% confidence interval [CI], 0.23-0.69; P=0.001), specific IgE levels to HDM ≥17.5 kU/L (OR, 1.85; 95% CI, 1.01-3.37; P=0.045), and duration of immunotherapy ≥3 years (OR, 7.37; 95% CI, 3.50-15.51; P<0.001) were identified as significant predictors of clinical remission during SCIT for patients with AR sensitized to HDM. Overall, 73 patients (24.0%) experienced adverse reactions to SCIT, and only 1 case of anaphylaxis (0.3%) developed. CONCLUSIONS: SCIT with HDM was found to be effective and safe for patients with AR. Specific IgE levels to HDM and a duration of SCIT ≥3 years may be predictors of clinical responses to SCIT in AR patients.

Abstrak :
Penelitian bioinformatika sering diterapkan untuk mempelajari penyakit dalam tubuh manusia. Penelitian yang sampai saat ini masih aktif dilakukan ialah penelitian terhadap pasien penderita kanker. Tujuan dari berbagai penelitian ini yaitu untuk menemukan pengobatan terbaik bagi pasien penderita kanker. Salah satu pengobatan yang baru ini muncul dikenal sebagai imunoterapi. Imunoterapi memungkinkan sel-sel imun tubuh kita sendiri digunakan untuk melawan sel-sel kanker. Instrumen utama dalam penelitian terhadap efektifitas imunoterapi juga kasus bioinformatika lainnya ialah data ekspresi gen. Namun, pada data ekspresi gen seringkali ditemukan nilai yang hilang atau missing values yang biasanya disebabkan oleh kerusakan gambar atau kesalahan dalam proses hibridisasi. Keberadaan missing values pada data ekspresi gen dapat menyebabkan kesulitan pada analisis lebih lanjut, di mana banyak analisis ekspresi gen memerlukan data yang lengkap seperti klasifikasi dan pengelompokan. Oleh karena itu, perlu dilakukan imputasi terhadap missing values agar analisis yang dilakukan dapat lebih akurat. Pada penelitian ini dilakukan imputasi menggunakan metode Bi-BPCA. Bi-BPCA merupakan metode imputasi dengan mengombinasikan analisis biclustering dan imputasi BPCA. Metode Bi-BPCA diterapkan pada data ekspresi gen di sekitar kanker setelah dilakukan imunoterapi. Setelah itu, performa dari metode Bi-BPCA dilihat dengan membandingkan hasil imputasi metode Bi-BPCA dengan metode imputasi lainnya diantaranya imputasi menggunakan rata-rata baris, rata-rata kolom, dan metode imputasi BPCA melalui nilai NRMSE. Selain itu, koefisien korelasi Pearson digunakan untuk menghitung korelasi antara nilai hasil imputasi metode Bi-BPCA dengan nilai aslinya. Berdasarkan penelitian ini metode Bi-BPCA menghasilkan NRMSE kurang dari 0.6 untuk missing rate 1-30%, lebih rendah dibandingkan NRMSE dari metode imputasi lainnya. Kemudian, metode Bi-BPCA menghasilkan nilai koefisien korelasi Pearson mayoritas di atas 0.9 mendekati 1. Hasil ini menunjukkan bahwa metode Bi-BPCA menghasilkan nilai imputasi yang lebih baik untuk menggantikan missing values dibandingkan dengan metode imputasi BPCA, rata-rata kolom, dan rata-rata baris. ......Bioinformatics research is often applied to study diseases in the human body. Research that is still actively being carried out is research on cancer patients. The aim of those studies is to find the best treatment for cancer patients. One treatment that has recently emerged is known as immunotherapy. Immunotherapy allows our body's own immune cells to be used to fight cancer cells. The main instrument in research on the effectiveness of immunotherapy as well as other cases of bioinformatics is gene expression data.. However, in gene expression data, it is often found missing values which are usually caused by image defects and errors in the hybridization process. The existence of missing values in gene expression data can cause difficulties in further analysis, where many analysis of gene expression requires complete data such as classification and clustering. Therefore, it is necessary to impute the missing values so that the analysis can be carried out more accurately. In this study, imputation was carried out using the Bi-BPCA method. Bi-BPCA is an imputation method by combining biclustering analysis and BPCA imputation. The Bi-BPCA method was applied to gene expression data around cancer after immunotherapy. After that, the performance of the Bi-BPCA method was seen by comparing the imputation results of the Bi-BPCA method with other imputation methods including imputation using row averages, column averages, and the BPCA imputation method through the NRMSE value. In addition, the Pearson correlation coefficient was used to calculate the correlation between the imputed value of the Bi-BPCA method and the original value. Based on this study, the Bi-BPCA method produces NRMSE values less than 0.6 for missing rates 1 to 30 percent, which is lower than NRMSE from other imputation methods. In addition, the Bi-BPCA method produces in a majority Pearson correlation coefficient above 0.9. These results indicate that the Bi-BPCA method produces better imputation values to replace the missing values.

Abstrak :
Innate and adaptive immunity play important roles in immunosurveillance and tumor destruction. This book discusses recent progress in innate immunity and Treg cells, and the regulation of innate immunity through Toll-like receptor (TLR) signalling.