To obtain tweets, do one of the following options:
Keep the query box empty, select number of tweets to display and select what type of document you want to export your tweets in. This will pull tweets from the RPI area.
Enter a query in the query box, select number of tweets and select what type of document you want to export your tweets in.


You were the original Great Khan of the Mongols, and formed the basis for what would soon become the largest contiguous empire in history shortly after your death. But in the early 13th Century, your lands weren't nearly what they would be someday, and the status quo hadn't yet been truly upended. That would quickly change, though, when a delegation from the Jin Dynasty arrived at your court in 1210 to proclaim the new emperor.


Ave is a general purpose programming language that compiles to Javascript. It aims to keep only the crucial parts of your code and get rid of the uneccessary ones, enforcing a clean, readable codebase.
fn greet(name)
console.log(`Hello world, this is ${name}!`)
greet('Ave') #Hello world, this is Ave!
Ave adds a layer of syntactic sugar over vanilla Javascript, adding tonnes of new features to increase productivity and lessen the load on you, as a developer. The indented block structure is Python inspired to make your code more readable.
enum Week
Monday, Tuesday, Wednesday,
Thursday, Friday, Saturday,
Sunday
console.log(Week.Monday) #Monday
Ave is completely open source. It's source code lives right here on github. Feel free to take a look and contribute, suggest changes or report bugs.
Assuming you've worked with javascript before, Ave is a piece of cake to master. If you every face any hassle, you can always refer to the documentation.
Ave compiles to ES6 Javascript, steaming and ready to be crunched by your favorite javascript runtimes environments. Think of it more as a syntax than a language !


Cryptococcus neoformans is a ubiquitous environmental fungus that can cause life-threatening meningitis and fungemia, often in the presence of acquired immunodeficiency syndrome (AIDS), liver cirrhosis, diabetes mellitus, or other medical conditions. To distinguish risk factors from comorbidities, we performed a hospital-based, density-sampled, matched case-control study.
All new-onset cryptococcal meningitis cases and cryptococcemia cases at a university hospital in Taiwan from 2002–2010 were retrospectively identified from the computerized inpatient registry and were included in this study. Controls were selected from those hospitalized patients not experiencing cryptococcal meningitis or cryptococcemia. Controls and cases were matched by admission date, age, and gender. Conditional logistic regression was used to analyze the risk factors.
A total of 101 patients with cryptococcal meningitis (266 controls) and 47 patients with cryptococcemia (188 controls), of whom 32 patients had both cryptococcal meningitis and cryptococcemia, were included in this study. Multivariate regression analysis showed that AIDS (adjusted odds ratio [aOR] = 181.4; p < 0.001), decompensated liver cirrhosis (aOR = 8.5; p = 0.008), and cell-mediated immunity (CMI)-suppressive regimens without calcineurin inhibitors (CAs) (aOR = 15.9; p < 0.001) were independent risk factors for cryptococcal meningitis. Moreover, AIDS (aOR = 216.3, p < 0.001), decompensated liver cirrhosis (aOR = 23.8; p < 0.001), CMI-suppressive regimens without CAs (aOR = 7.3; p = 0.034), and autoimmune diseases (aOR = 9.3; p = 0.038) were independent risk factors for developing cryptococcemia. On the other hand, diabetes mellitus and other medical conditions were not found to be risk factors for cryptococcal meningitis or cryptococcemia.
The findings confirm AIDS, decompensated liver cirrhosis, CMI-suppressive regimens without CAs, and autoimmune diseases are risk factors for invasive C. neoformans diseases.
Cryptococcus neoformans is a pathogenic fungus that causes life-threatening meningitis, the first case of which was reported in 1905 [ 1]. C. neoformans is ubiquitous [ 2]. The Centers for Disease Control and Prevention (CDC) of the United States estimated that there are approximately one million new cryptococcal meningitis cases every year worldwide, with more than 70% of these cases occurring in sub-Saharan Africa [ 3]. C. neoformans infection is therefore an important global health concern [ 4].
Current understanding of the pathogenesis of invasive cryptococcal diseases is primarily based on clinical case series [ 5– 11] and mouse experiments [ 12– 17], which suggest that host conditions that impair cell-mediated immunity (CMI) (e.g., human immunodeficiency virus [HIV] infection with acquired immunodeficiency syndrome [AIDS], immunosuppressive therapy) play a critical role. Liver cirrhosis has also been reported as a condition that may increase the risk of cryptococcosis [ 18]. Other reported possible risk factors include diabetes mellitus, lymphoproliferative malignancy, hematological malignancy, cancer, autoimmune diseases, and lung diseases [ 19– 21]. However, ascertainment of a condition as a risk factor for a disease requires either a cohort study (to compare the incidence of disease between those with the condition and those without) or a case-control study (to compare the proportion of the condition between those with the disease and those without), in order to distinguish true risk factors from comorbidities. To date, no cohort study or case-control study has been conducted to examine the risk factors of invasive C. neoformans diseases.
The first case of cryptococcal meningitis in Taiwan was diagnosed in 1957 [ 22]. Large clinical case series on cryptococcal meningitis [ 23, 24], cryptococcemia [ 25] and cryptococcal diseases [ 26] reported high rates of HIV/AIDS, immunosuppressive therapy, decompensated liver cirrhosis, malignancy, diabetes mellitus, and kidney diseases among the case patients. To distinguish risk factors from comorbidities, we performed a hospital-based, retrospective, density-sampled, matched case-control study.
This study was conducted at National Taiwan University Hospital (Taipei, Taiwan), a university-affiliated medical center with a 2,200-bed capacity, which provides both primary and tertiary referral care in northern Taiwan.
This was a retrospective, density-sampled, case-control study. Patients with cryptococcal meningitis or cryptococcemia who were diagnosed and hospitalized during 2002–2010 (cases) were compared with those who were hospitalized during the same time period but did not have cryptococcal meningitis or cryptococcemia (controls). The cases and controls were matched according to admission date, age, and gender.
Patient medical records were retrospectively reviewed to obtain information on diagnosis, sites of C. neoformans infection, and potential risk factors. All personal information was anonymized. The study procedures were reviewed and approved by National Taiwan University Hospital’s institutional review board (No. 201101083RC). The institutional review board approved the exemption of informed consent.
All of the patients with the ICD-9 diagnostic code 117.5 (cryptococcal diseases) upon either admission or discharge from January 1, 2002 to December 31, 2010 were identified using a computerized registry of inpatients. The patients’ medical records and microbiological reports were reviewed. All of the new-onset cases of C. neoformans meningitis (cryptococcal meningitis, confirmed by cerebrospinal fluid [CSF] culture) or C. neoformans fungemia (cryptococcemia, confirmed by blood culture) were included in the present study.
The controls were selected from inpatients who did not have cryptococcal meningitis or cryptococcemia; they were individually matched to each case by admission date, age (within a 5-year range), and gender at a 2:1 (cryptococcal meningitis) or a 4:1 (cryptococcemia) ratio. We first obtained the list of 600,782 admissions during the period from January 1, 2002 to December 31, 2010 using a computerized registry of inpatients. We then randomly selected controls for each case from the inpatients who met the matching criteria, using a random number generator.
The medical records were systematically reviewed for information regarding age, gender, and the presence of underlying diseases or conditions before the onset of invasive cryptococcal diseases. We assumed an induction time (i.e., the minimum time needed for a causal factor to induce the disease) of one month. Only those conditions that had been present at least one month prior to the onset of the cryptococcal diseases were included in this study.
The data were collected using a standardized recording format, which included items regarding the presence or absence of the following conditions: AIDS, decompensated liver cirrhosis, uremia, cytotoxic chemotherapy, CMI-suppressive therapy, organ transplantation, diabetes mellitus, lymphoma, leukemia/myeloma, solid cancer, other malignancies (e.g., gastrointestinal stromal tumor [GIST], sarcoma, thymoma), autoimmune diseases, cardiovascular disease, chronic obstructive pulmonary disease, asthma, bronchiectasis, pneumoconiosis, and gastrointestinal diseases. All of the data were independently verified by a second researcher.
In addition, the medical records were reviewed for a history of close contact with pigeons before the onset of the invasive cryptococcal diseases, including raising pigeons or visiting pigeon farms, if this information was recorded.
AIDS was defined using the CDC’s 1993 revised case definition [ 27]. Liver cirrhosis was considered to be decompensated if the Child-Pugh score [ 28] was B or C. CMI-suppressive therapy was defined to include corticosteroids, azathioprine, mycophenolate mofetil, cyclosporine, tacrolimus and other immunosuppressive drugs that inhibit T-cell functions. CMI-suppressive therapy was further classified to stipulate whether a regimen was prescribed with or without calcineurin inhibitors (CAs) (cyclosporine or tacrolimus), which have direct in vitro antifungal activity against C. neoformans [ 29]. Diabetes mellitus was defined as having a fasting plasma glucose level ≥ 126 mg/dL, having a random plasma glucose level ≥ 200 mg/dL, or already receiving antidiabetic agents or insulin to control sugar [ 30]. Uremia was defined as end-stage renal disease with uremic symptoms or as receiving dialysis for more than three months. Autoimmune diseases included systemic lupus erythematosus, rheumatoid arthritis, dermatomyositis, and pemphigus, among others.
Statistical analyses were performed using SAS 9.2 (SAS Institute, Cary, North Carolina, USA). When two proportions were being compared, a chi-square test was used. Fisher’s exact test was used when any value in the cells of the contingency table was smaller than five. Between-group differences for continuous data were compared using Wilcoxon rank sum test. Conditional logistic regression was used to analyze the risk factors. The exact method was used. All variables with p < 0.10 in the univariate analysis were included in the maximum model and underwent stepwise selection during the multivariate analyses. All statistical tests were two-tailed, and p < 0.05 was considered statistically significant.
From January 1, 2002 through December 31, 2010, a total of 276 inpatients at National Taiwan University Hospital had the ICD-9 diagnostic code 117.5 upon admission or discharge. Of them, 116 had new-onset cryptococcal meningitis (n = 101) or new-onset cryptococcemia (n = 47), including 32 who had simultaneous cryptococcal meningitis and cryptococcemia. The remaining 160 patients did not meet the inclusion criteria, including those with pulmonary cryptococcosis (n = 120), other local involvement (n = 3), non- Cryptococcus neoformans fungemia (n = 1), an unspecified diagnosis (positive for serum cryptococcal antigen, but without a culture or histopathological confirmation; n = 17), an incomplete work-up (n = 3), an old diagnosis (n = 10), or a mis-coding (n = 6). Fig. 1 shows the flow chart of the recruitment of cases.
A total of 326 controls were randomly selected from the 600,782 admissions during the period from January 1, 2002 through December 31, 2010, including 188 controls who were matched to the 47 patients with cryptococcemia (at a 4:1 ratio) and the 138 controls who were matched to the 69 patients who had cryptococcal meningitis but did not have cryptococcemia (at a 2:1 ratio).
Table 1 shows the characteristics of cryptococcal meningitis and cryptococcemia cases, including demographic features, underlying diseases, history of immunosuppressive therapy, and close contact with pigeons.
| Age, range, years | 20–86 | 24–79 | |
| Age, mean ± SD, years | 49.8 ± 17.2 | 51.6 ± 18.2 | |
| Male | 73 (72.3) | 36 (76.6) | 0.58 |
| AIDS | 42 (41.6) | 21 (44.7) | 0.72 |
| Immunosuppressive therapy | 24 (23.8) | 13 (27.7) | 0.68 |
| CMI-suppressive therapy | 23 (22.8) | 13 (27.7) | 0.52 |
| Regimens without CAs | 19 (18.8) | 11 (23.4) | 0.52 |
| Prednisolone a | 11 | 5 | |
| Methylprednisolone a | 1 | 1 | |
| Prednisolone a + azathioprine | 4 | 3 | |
| Prednisolone a + chlorambucil | 1 | 0 | |
| Prednisolone a + cyclophosphamide | 1 | 1 | |
| Prednisolone a + rituximab + etoposide | 1 | 0 | |
| Dexamethasone a + mephalan | 0 | 1 | |
| CA-based regimens | 4 (4.0) | 2 (4.3) | 1.00 |
| Tarcolimus + prednisolone b + mycophenolate mofetil | 3 | 1 | |
| Cyclosporin + prednisolone b | 1 | 0 | |
| Cyclosporin + methylprednisolone b | 0 | 1 | |
| Cytotoxic chemotherapy | 5 (5.0) | 3 (6.4) | 0.71 |
| Cardiovascular disease | 21 (20.8) | 13 (27.7) | 0.36 |
| Autoimmune diseases | 13 (12.9) | 10 (21.3) | 0.19 |
| Decompensated liver cirrhosis | 8 (7.9) | 8 (17.0) | 0.10 |
| Diabetes mellitus | 16 (15.8) | 8 (17.0) | 0.86 |
| Gastrointestinal diseases | 6 (5.9) | 6 (12.8) | 0.16 |
| Lymphoma | 4 (4.0) | 3 (6.4) | 0.68 |
| Leukemia/myeloma | 3 (3.0) | 3 (6.4) | 0.38 |
| Cancer | 14 (13.9) | 6 (12.8) | 1.00 |
| Solid organ transplantation | 4 † (4.0) | 1 * (2.1) | 1.00 |
| Bone marrow/stem cell transplantation | 0 (0) | 0 (0) | - |
| Uremia | 2 (2.0) | 1 (2.1) | 1.00 |
| COPD | 0 (0) | 0 (0) | - |
| Asthma | 0 (0) | 0 (0) | - |
| Bronchiectasis | 0 (0) | 0 (0) | - |
| Pneumoconiosis | 1 (1) | 0 (0) | 1.00 |
| Close contact with pigeons | 5 (5.0) | 0 (0) | 0.31 |
Data are no. (%) of patients, unless otherwise indicated. AIDS: acquired immunodeficiency syndrome; CAs: calcineurin inhibitors; CMI: cell-mediated immunity; COPD: chronic obstructive pulmonary disease.
†Heart (n = 2), kidney (n = 1), liver (n = 1).
*Heart (n = 1).
a Mean dosage of steroid in CMI-suppressive regimens without CA: equivalent dose of prednisolone 20 mg/day in meningitis cases and 30 mg/day in cryptococcemia cases.
b Mean dosage of steroid in CA-based regimens: equivalent dose of prednisolone 10 mg/day in meningitis cases and 55 mg/day in cryptococcemia cases.
The mean age of cryptococcal meningitis and cryptococcemia cases was approximately 50 years. Most cases (72.3%–76.6%) occurred in men. The age and gender distributions were similar between cases of cryptococcal meningitis and those of cryptococcemia ( Table 1). The majority of patients younger than 40 years had AIDS, whereas the older age (≥50 years) group consisted primarily of non-AIDS patients.
AIDS (41.6%–44.7%) was the most common underlying condition in both the cryptococcal meningitis cases and the cryptococcemia cases, followed by immunosuppressive therapy (23.8%–27.7%), cardiovascular diseases (20.8%–27.7%), autoimmune diseases (12.9%–21.3%), decompensated liver cirrhosis (7.9%–17.0%), and diabetes mellitus (15.8%–17.0%). The pattern of underlying conditions was not significantly different between the cryptococcal meningitis cases and the cryptococcemia cases ( Table 1).
In-hospital mortality was significantly higher in cryptococcemia cases compared with cryptococcal meningitis cases (23/47 [48.9%] vs. 28/101 [27.7%], p = 0.016). Of the 101 patients with cryptococcal meningitis, 32 (32%) had cryptococcemia, for whom in-hospital mortality occurred at double the rate of those who had cryptococcal meningitis but did not have cryptococcemia (14/32 [43.8%] vs. 14/69 [20.3%], p = 0.027). Cases with decompensated liver cirrhosis had a particularly high mortality, compared with cases without decompensated liver cirrhosis, in both cryptococcal meningitis group (6/8 [75.0%] vs. 22/93 [23.7%], p = 0.005) and cryptococcemia group (6/8 [75.0%] vs. 17/39 [43.6%], p = 0.137).
Table 2 shows the concomitantly involved sites in the 47 patients with cryptococcemia. Those with AIDS (n = 21) were more likely to have culture-proven meningitis than those with decompensated liver cirrhosis (n = 8) (19/21 [90%] vs. 3/8 [44.4%], p = 0.008). However, those patients with decompensated liver cirrhosis were significantly less likely than patients with AIDS to undergo a lumbar puncture for a CSF study (5/8 [62.5%] vs. 21/21 [100%], p = 0.023; Table 2).
| Meningitis | 32 (68.1) | 3 (37.5) | 19 (90) | 0.008 |
| CSF culture (+) | 31 (66.0) | 3 (37.5) | 19 (90) | - |
| CSF Cryptococcal Ag (+) | 32 (68.1) | 3 (37.5) | 19 (90) | - |
| CSF culture (−) | 5 (10.6) | 2 (25.0) | 2 (10) | 0.568 |
| CSF not checked | 8 (17.0) | 3 (37.5) | 0 (0) | 0.023 |
| Peritonitis | 3 (6.4) | 3 (37.5) | 1 (5) | 0.076 |
| Pleurisy | 3 (6.4) | 2 (25.0) | 0 (0) | 0.089 |
| Lung (pathology-proven) | 2 (4.3) | 0 (0) | 0 (0) | 1.000 |
| Urine | 7 (14.9) | 3 (37.5) | 2 (10) | 0.112 |
| Bone and soft tissue | 1 (2.1) | 0 (0) | 0 (0) | 1.000 |
| PTCD | 1 (2.1) | 1 (12.5) | 0 (0) | 0.310 |
PTCD: Percutaneous transhepatic cholangio-drainage.
ξ p-values were computed using Fisher’s exact test to compare cryptococcemia cases with decompensated liver cirrhosis and cases with AIDS.
†Culture-proven, unless otherwise indicated.
The significant variables in the univariate analysis included AIDS, decompensated liver cirrhosis, CMI-suppressive regimens without CA, cytotoxic chemotherapy, cardiovascular disease, autoimmune diseases, cancer, and close contact with pigeons ( Table 3). Diabetes mellitus was not a risk factor (crude odds ratio [OR] = 1.5; 95% CI: 0.7 to 3.2; p = 0.389). Multivariate regression analysis revealed the following three independent risk factors for cryptococcal meningitis: decompensated liver cirrhosis (adjusted OR = 8.5; 95% CI: 1.6 to 62.3; p = 0.008), AIDS (adjusted OR = 181.4; 95% CI: 28.2 to >999; p < 0.001), and CMI-suppressive regimens without CAs (adjusted OR = 15.9; 95% CI: 4.9 to 68.2; p < 0.001) ( Table 4). Close contact with pigeons was a risk factor for cryptococcal meningitis in the univariate analysis (crude OR = 13.5; 95% CI: 1.8 to ∞; p = 0.008); however, this variable did not enter the final model.
| Decompensated liver cirrhosis | 8 | 4 | 6.5 (1.5–39.4) | 0.009 |
| AIDS | 42 | 3 | 118.8 (20.0–>999) | <0.001 |
| Immunosuppressive therapy | 24 | 57 | - | - |
| CMI-suppressive therapy | 23 | 15 | - | - |
| Regimens without CAs # | 19 # | 10 # | 5.5 (2.3–13.9) | <0.001 |
| CA-based regimens | 4 | 5 | 1.7 (0.3–8.1) | 0.630 |
| Cytotoxic chemotherapy | 5 | 47 | 0.2 (0.1–0.7) | 0.002 |
| Solid organ transplantation | 4 † | 5 * | 1.9 (0.4–8.8) | 0.556 |
| Bone marrow/stem cell transplantation | 0 | 1 | 2.0 (0–78) | 1.000 |
| Diabetes mellitus | 16 | 30 | 1.5 (0.7–3.2) | 0.389 |
| Cardiovascular disease | 21 | 83 | 0.5 (0.2–0.9) | 0.026 |
| Uremia | 2 | 4 | 1.2 (0.1–8.9) | 1.000 |
| Gastrointestinal diseases | 6 | 24 | 0.9 (0.3–2.5) | 1.000 |
| Autoimmune diseases | 13 | 8 | 4.6 (1.7–12.9) | 0.001 |
| COPD | 0 | 5 | 0.6 (0–3.3) | 0.655 |
| Asthma | 0 | 5 | 0.4 (0–2.1) | 0.379 |
| Bronchiectasis | 0 | 2 | 1.7 (0–21.3) | 1.000 |
| Pneumoconiosis | 1 | 0 | 2.0 (0.1–∞) | 0.667 |
| Lymphoma | 4 | 5 | 2.2 (0.4–10.3) | 0.422 |
| Leukemia/myeloma | 3 | 5 | 2.8 (0.5–15.6) | 0.271 |
| Cancer | 14 | 85 | 0.3 (0.1–0.6) | <0.001 |
| Others (GIST/sarcoma/thymoma) | 0 | 5 | 0.5 (0–3.7) | 0.546 |
| Close contact with pigeons | 5 | 0 | 13.5 (1.8–∞) | 0.008 |
CMI: cell-mediated immunity; CAs: calcineurin inhibitors; COPD: chronic obstructive pulmonary disease; GIST: gastrointestinal stromal tumor.
†Heart (n = 2), kidney (n = 1), liver (n = 1).
* Heart (n = 2), kidney (n = 2), liver (n = 1).
# The mean dosage of steroid was significantly higher in cases received CMI-suppressive regimens without CA (n = 19) than that in controls received CMI-suppressive regimens without CA (n = 10) (equivalent dose of prednisolone: 20 vs. 5.4 mg/day, p = 0.041).
| AIDS | 181.4 (28.2–>999) | <0.001 |
| CMI-suppressive regimens without CAs | 15.9 (4.9–68.2) | <0.001 |
| Decompensated liver cirrhosis † | 8.5 (1.6–62.3) | 0.008 |
AIDS: acquired immunodeficiency syndrome. CMI: cell-mediated immunity; CAs: calcineurin inhibitors.
†Decompensated liver cirrhosis: Child-Pugh score of B or C.
Univariate analyses identified AIDS, decompensated liver cirrhosis, CMI-suppressive regimens without CAs, autoimmune diseases, and cancer as the significant variables ( Table 5). Diabetes mellitus was not a risk factor (crude OR = 1.4; 95% CI: 0.5 to 3.5; p = 0.650). Decompensated liver cirrhosis (adjusted OR = 23.8; 95% CI: 3.4 to 340.9; p < 0.001), AIDS (adjusted OR = 216.3; 95% CI: 24.2 to >999; p < 0.001), CMI-suppressive regimens without CAs (adjusted OR = 7.3; 95% CI: 1.1 to 57.5; p = 0.034), and autoimmune diseases (adjusted OR = 9.3; 95% CI: 1.1 to 135.7; p = 0.038) were independent risk factors for cryptococcemia ( Table 6).
| Decompensated liver cirrhosis | 8 | 4 | 13.7 (2.7–134.6) | <0.001 |
| AIDS | 21 | 2 | 81.5 (13.1–>999) | <0.001 |
| Immunosuppressive therapy | 13 | 40 | - | - |
| CMI-suppressive therapy | 13 | 11 | - | - |
| Regimens without CAs # | 11 # | 9 # | 5.7 (2.0–17.6) | <0.001 |
| CA-based regimens | 2 | 2 | 4.0 (0.3–55.2) | 0.362 |
| Cytotoxic chemotherapy | 3 | 31 | 0.3 (0.1–1.2) | 0.106 |
| Solid organ transplantation | 1 † | 2 * | 2.0 (0.03–38.4) | 0.980 |
| Bone marrow/stem cell transplantation | 0 | 0 | - | - |
| Diabetes mellitus | 8 | 25 | 1.4 (0.5–3.5) | 0.650 |
| Cardiovascular disease | 13 | 69 | 0.6 (0.2–1.4) | 0.252 |
| Uremia | 1 | 5 | 0.8 (0.02–8.4) | 1.000 |
| Gastrointestinal diseases | 6 | 21 | 1.2 (0.3–3.6) | 0.935 |
| Autoimmune diseases | 10 | 9 | 5.8 (1.9–19.9) | 0.002 |
| COPD | 0 | 6 | 0.5 (0–2.6) | 0.492 |
| Asthma | 0 | 5 | 0.6 (0–3.3) | 0.655 |
| Bronchiectasis | 0 | 1 | 4.0 (0–76) | 1.000 |
| Pneumoconiosis | 0 | 0 | - | - |
| Lymphoma | 3 | 5 | 2.6 (0.4–15.8) | 0.394 |
| Leukemia/myeloma | 3 | 2 | 6.0 (0.7–71.8) | 0.116 |
| Cancer | 6 | 61 | 0.3 (0.1–0.8) | 0.008 |
| Others (GIST/sarcoma/thymoma) | 0 | 3 | 1.0 (0–6.9) | 1.000 |
CMI: cell-mediated immunity; CAs: calcineurin inhibitors; COPD: chronic obstructive pulmonary disease; GIST: gastrointestinal stromal tumor.
†Heart (n = 1).
*kidney (n = 1), liver (n = 1).
# The mean dosage of steroid was significantly higher in cases CMI-suppressive regimens without CA (n = 11) than that in controls received CMI-suppressive regimens without CA (n = 9) (equivalent dose of prednisolone: 30 mg/day vs. 5 mg/day, p = 0.003).
| AIDS | 216.3 (24.2–>999) | <0.001 |
| CMI-suppressive regimens without CAs | 7.3 (1.1–57.5) | 0.034 |
| Autoimmune diseases | 9.3 (1.1–135.7) | 0.038 |
| Decompensated liver cirrhosis † | 23.8 (3.4–340.9) | <0.001 |
AIDS: acquired immunodeficiency syndrome. CMI: cell-mediated immunity. CAs: calcineurin inhibitors.
†Decompensated liver cirrhosis: Child-Pugh score of B or C.
To our knowledge, the present study is the first hospital-based, case-control study to investigate the risk factors for the occurrence of invasive C. neoformans diseases. The results showed that AIDS, decompensated liver cirrhosis, and CMI-suppressive regimens without CAs were three independent risk factors for cryptococcal meningitis and cryptococcemia in Taiwan. Moreover, autoimmune disease was an independent risk factor for cryptococcemia. On the other hand, diabetes mellitus and other medical conditions were not found to be risk factors of cryptococcal meningitis or cryptococcemia.
Both cryptococcal meningitis and cryptococcemia were included in the present study as invasive C. neoformans diseases cases. We had previously reported that cryptococcemia is a fulminant form of cryptococcal disease with a high acute mortality rate, especially for those with liver cirrhosis [ 25]. The present study further highlights that patients with cryptococcemia have an approximately two-fold higher mortality rate than patients who have had cryptococcal meningitis unaccompanied by cryptococcemia.
AIDS, the end stage of HIV infection [ 27], is characterized by profound impairment of CMI [ 5– 11], which predisposes people to invasive C. neoformans diseases. Extrapulmonary cryptococcosis is an AIDS-defining illness [ 27]. Cryptococcal meningitis is one of the most common opportunistic infections in patients who develop AIDS [ 3, 4]. The wide use of highly active antiretroviral therapy (HAART), which can help prevent the development of AIDS if initiated early in the course of HIV infection, led to a decline in the number of C. neoformans cases in North America and Western Europe [ 20, 31]. Our study provides new epidemiologic evidence that confirmed that AIDS is an important risk factor for the occurrence of invasive C. neoformans diseases. Our results support the World Health Organization’s current advice on the prevention of cryptococcal diseases in HIV-infected patients, which emphasizes that the most important and cost-effective strategy is the early initiation of ART through expanded HIV testing and scaled-up access to HAART [ 4].
CMI has been shown to play a critical role in the host’s defense against C. neoformans in animal models [ 12– 17]. Our study confirmed that CMI-suppressive therapy increases the risk of invasive C. neoformans diseases in humans. Of particular interest is the observation that only the regimen that did not contain a calcineurin inhibitor was found to be a significant risk factor. The virulence of C. neoformans depends on fungal calcineurin [ 32]. Calcineurin inhibitors, such as cyclosporine and tacrolimus, have in vitro antifungal activity against C. neoformans [ 29, 33] and may mitigate the increased risk of C. neoformans diseases under CMI-suppressive therapy. However, because of the small numbers of subjects receiving cyclosporine- or tacrolimus-based CMI-suppressive regimens in the present study, whether such regimens actually did confer a lower risk of invasive C. neoformans diseases remains statistically inconclusive and needs to be clarified in future studies. It is advisable that all patients receiving CMI-suppressive therapy, regardless of their regimens, be educated to avoid exposure to environmental sources of C. neoformans, such as pigeons and Eucalyptus trees. Physicians should be aware of the risk of invasive C. neoformans diseases in these patients. Early diagnosis and prompt antifungal treatment can be life-saving.
Patients with autoimmune diseases, such as systemic lupus erythematosus (SLE), have been demonstrated to have defects in the functions of phagocytes, humoral immunity, and cellular immunity [ 34]. In a study involving 150 SLE patients, the functional impairment of T helper cells was found to be correlated with disease activity rather than the medication doses [ 34], which indicates that autoimmune disease per se is an independent factor that contributes to decreased CMI. In the present study, we confirmed autoimmune disease is an independent risk factor for the occurrence of cryptococcemia.
In the present study, we confirmed that decompensated liver cirrhosis is an independent risk factor for the occurrence of invasive C. neoformans disease. The pathogenesis mechanism could involve multiple aspects. First, although C. neoformans typically enters the human body via inhalation through the respiratory system, people may become infected by ingesting contaminated food [ 35]. The presence of collateral circulation in decompensated liver cirrhosis allows for ingested C. neoformans to bypass the liver scavenger system and directly enter the circulatory system, thereby causing cryptococcemia and being further disseminated into the central nervous system. In addition, deficiencies in complement [ 36] and chemotaxis [ 37] as well as lymphocyte hyporesponsiveness [ 38] have been reported. The impaired innate and cell-mediated immunity in persons with decompensated liver cirrhosis not only contributes to an increased risk for invasive cryptococcal disease, but also a high risk of mortality once the disease occurs [ 25]. The high mortality of patients with decompensated liver cirrhosis in the present study (6/8 [75%] in cryptococcal meningitis cases and 6/8 [75%] in cryptococcemia cases) is consistent with that reported by Jean et al. (9/11 [82%]) [ 25] and Singh et al. (26/32 [81%]) [ 18]. Whether early recognition and prompt antifungal therapy can reduce this high mortality remains to be determined.
Diabetes mellitus was present in 8.5% to 33% of cryptococcosis cases in reported series [ 21, 23, 26, 39] and in 15.8% of cryptococcal meningitis cases and 17.0% of cryptococcemia cases in the present study. Nevertheless, diabetes mellitus is a relative common condition in population, and the prevalence increases with age (7.56% among Taiwanese men aged 40–59, 19.97% among Taiwanese men aged 60–79, in Year 2009) [ 40]. This highlights the necessity of using an age-matched control group in evaluating the role of diabetes. The lack of association between diabetes mellitus and cryptococcosis in the present case-control study implies that diabetes mellitus was a comorbidity in those with two diseases, and that diabetic patients are actually not at increased risk of invasive cryptococcal diseases.
The strengths of the present study include the use of a computerized inpatient registry and ICD-9 diagnostic codes to identify all cases of invasive C. neoformans diseases during the study period and the verification of the diagnoses through review of medical records and microbiologic reports. In addition, a standard data format was used to systematically collect information on potential risk factors from medical records. This method circumvents patient recall bias, which is commonly encountered in case-control studies.
Our study has several limitations. First, because the medical records may not have included comprehensive information on casual exposure to pigeons or Eucalyptus trees, we were unable to confirm that such exposure is a risk factor for invasive C. neoformans disease. Second, close contact with pigeons (including raising pigeons or visiting pigeon farms; n = 5) likely is an important factor in acquiring C. neoformans disease, and it was shown to be a risk factor in the univariate analysis (OR = 13.5, p = 0.008). However, the small number of cases limits the statistical power of the multivariate analysis to implicate close contact with pigeons as an independent risk factor.
In conclusion, AIDS, decompensated liver cirrhosis, CMI-suppressive regimens without CAs, and autoimmune diseases are four independent risk factors for the occurrence of invasive C. neoformans diseases, while diabetes mellitus and other medical conditions are not. The present study confirms previous clinical observations and animal studies on the critical role of impaired cell-mediated immunity in the pathogenesis of invasive C. neoformans diseases, and provides a more precise characterization of high-risk individuals.
(RAR)
Click here for additional data file.


|
OpenJij
0.0.8
|
naive TransverseIsing structure with discrete-time trotter spins (no Eigen implementation) More...
#include <transverse_ising.hpp>
Public Types | |
| using | system_type = transverse_field_system |
| using | FloatType = typename GraphType::value_type |
Public Member Functions | |
| TransverseIsing (const TrotterSpins &init_trotter_spins, const GraphType &init_interaction, FloatType gamma) | |
| TransverseIsing Constructor. More... | |
| TransverseIsing (const graph::Spins &classical_spins, const GraphType &init_interaction, FloatType gamma, size_t num_trotter_slices) | |
| TransverseIsing Constuctor with initial classical spins. More... | |
| void | reset_spins (const TrotterSpins &init_trotter_spins) |
| reset spins with trotter spins More... | |
| void | reset_spins (const graph::Spins &classical_spins) |
| reset spins with trotter spins More... | |
Public Attributes | |
| TrotterSpins | trotter_spins |
| trotterlized spins More... | |
| const GraphType | interaction |
| interaction More... | |
| std::size_t | num_classical_spins |
| number of real classical spins (dummy spin excluded) More... | |
| FloatType | gamma |
| coefficient of transverse field term More... | |
naive TransverseIsing structure with discrete-time trotter spins (no Eigen implementation)
| GraphType | |
| eigen_impl | specify that Eigen implementation is enabled. |
| using openjij::system::TransverseIsing< GraphType, eigen_impl >::FloatType = typename GraphType::value_type |
| using openjij::system::TransverseIsing< GraphType, eigen_impl >::system_type = transverse_field_system |
|
inline |
TransverseIsing Constructor.
| init_trotter_spins | |
| init_interaction |
|
inline |
TransverseIsing Constuctor with initial classical spins.
| classical_spins | initial classical spins |
| init_interaction | |
| num_trotter_slices |
|
inline |
reset spins with trotter spins
| classical_spins |
|
inline |
reset spins with trotter spins
| init_trotter_spins |
| FloatType openjij::system::TransverseIsing< GraphType, eigen_impl >::gamma |
coefficient of transverse field term
| const GraphType openjij::system::TransverseIsing< GraphType, eigen_impl >::interaction |
interaction
| std::size_t openjij::system::TransverseIsing< GraphType, eigen_impl >::num_classical_spins |
number of real classical spins (dummy spin excluded)
| TrotterSpins openjij::system::TransverseIsing< GraphType, eigen_impl >::trotter_spins |
trotterlized spins


Raise on hover from flat
Try Me
Flatten on hover from raised
Try Me
Raise from Less flat position on hover
Try Me
Lift sides on Hover
Try Me
Flatten sides on hover
Try Me
Curl right corner on hover
Try Me
Curl right side on hover
Try Me
Curl bottom corners on hover
Try Me
Group examples
Raise on hover
Button One
Button Two
Button Three
Flatten on hover
Button One
Button Two
Button Three
Less flat raise on hover
Button One
Button Two
Button Three
Lift sides on hover
Button One
Button Two
Button Three
Flatten sides on hover
Button One
Button Two
Button Three
Curl right corner on hover
Button One
Button Two
Button Three
Curl right side on hover
Button One
Button Two
Button Three
Curl bottom corners on hover
Button One
Button Two
Button Three
更多网页特效，请访问
网页特效库
,欢迎加入网页特效库QQ交流群：258242983


This portfolio is being created and upgraded by me through the Google Software Product Sprint program during Summer 2021.
I am so excited to share the growth of my skills on here, and am thrilled to be a part of this program looking to help me explore a lasting set of skills that will also help me develop connections to other students like me who are passioante, inquisitive, and driven
You can check out more of the work on Github below:


With the founders reward, zcash is a regulatable security.
More fun, I will be publishing a paper on how law enforcement can trace it later this year.
Sorry. Privacy is more than what computer geeks think it is. Oh, I used to do forensics for the Fed's. Not so hard.


BEWARE: spocc provides you a nice interface to many data providers for species occurrence data. However, in cases where you request data from GBIF in addition to other data sources, there could be duplicate records. This is because GBIF is, to use an ecology analogy, a top predator, and pulls in data from lower nodes in the food chain. For example, iNaturalist provides data to GBIF, so if you search for occurrence records for Pinus contorta from iNaturalist and GBIF, you could get, for example, 20 of the same records.
We think a single R interface to many occurrence record providers will provide a consistent way to work with occurrence data, making analyses and vizualizations more repeatable across providers.
For cleaning data, see packages scrubr
(https://cran.r-project.org/package=scrubr) and CoordinateCleaner
(https://cran.r-project.org/package=CoordinateCleaner)
Do get in touch with us if you have concerns, have ideas for eliminating duplicates


Identify individual developmental needs and implement customized coaching and mentoring to help students master new skills. Succeed in helping students increase their programming skills within a week using Scratch software.
Created schedule system to help faculty and student to manage their time. Maintained website by ensuring that program details, announcement, and information was accurate. Reply to numerous inquiries by phone or email and design marketing materials for the department
Collaboratively administrate empowered markets via plug-and-play networks. Dynamically procrastinate B2C users after installed base benefits. Dramatically visualize customer directed convergence without revolutionary ROI.
Developed affordable, effective Radio Control car platform (Nuccar) with high processing power and 3D perception. Used Intel Nuc to program GPS mapping and control system to run at various speeds.
GPA: 3.31
GPA: 3.4
Explored Japanese culture and volunteered with Japanese High school students to improve their English communication skills.
Researched Arduino, and Raspberry Pi to measure a way to improve air quality
Apart from working, I enjoy most of my time being outdoors. I enjoy mountain biking, running, hiking and kayaking.
I also love traveling. I have traveled to 7 countries: Japan, Vietnam, South Korea, Taiwan, Thailand, Malaysia, and USA. My goal is to travel up tp 50 countries before I reach 35 :)