Purpose: Cervical cancer caused by human papillomavirus (HPV) is a public health problem. The aim of the study was to develop a low-cost and reliable genotyping test of HPV for resource-limited settings. Materials and methods: This observational study was done in a cancer hospital in eastern India. Nonpregnant women with intact uteri (age: 25–65 years) were screened by testing their cervical swabs using the hybrid capture 2 (HC2) assay (HC2; Qiagen). HPV genotyping was done using a laboratory-developed test [LDT-nested multiplex endpoint polymerase chain reaction (PCR) assay]. The results of LDT were verified using HC2 genotypic assay (Qiagen). The t-test was used to ascertain statistical significance. Results: A total of 253 out of 2,502 (10.11%) individuals tested positive for HPV by the HC2 assay. Out of these 253 HC2-positive samples, genotyping was successful by nested multiplex end point PCR in 182 (72%) of the samples. The commonest genotypes were the type 16 in 21.3% of samples and type 18 in 14.6% of samples. Among the non-16/18 genotypes, type 68 was the most prevalent (15.4% of samples). We detected single HPV genotypes in 123 out of 182 samples (68%), two genotypes in 44 out of 182 (24%), and three genotypes in 13 out of 182 (7%) samples. Two samples yielded four genotypes (1%). The cost of HPV genotyping by this nested multiplex endpoint PCR was Rs. 840 ($10.51). The cost of HPV genotyping by Sanger-based deoxyribonucleic acid (DNA) sequencing was Rs. 4,456 ($55.76), next-generation sequencing (NGS) Rs. 5,000 ($62.56), and that of HC2 test-based genotyping (using Qiagen kits) was Rs. 1,120 ($14.01) per positive sample. Conclusion: The study provides important epidemiological information and shows that nested multiplex endpoint PCR-based methods may be used in HPV genotyping in resource-limited settings. The results are significant for surveillance and vaccination strategies.

Context: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a significant pandemic, claiming many lives. Controlling the infection posed a great challenge, which was addressed by the development of vaccines against the virus. However, the disease continued to spread, resulting in breakthrough infections. Consequently, understanding the risk factors and severity of breakthrough infections became a major concern. Aims: (1) To measure the incidence of SARS-CoV-2 breakthrough infection among fully vaccinated medical students; (2) to determine the risk factors for breakthrough SARS-CoV-2 infection in vaccinated medical students; (3) to find out the severity of illness among students with breakthrough infection. Settings and design: This was a cross-sectional study carried out on undergraduate medical students at a teaching hospital in Puducherry. Study subjects were identified by simple random sampling. Materials and methods: A total of 215 undergraduate medical students vaccinated with two doses of the coronavirus disease 2019 (COVID-19) vaccine were included in the study. The questionnaire consisted of demographic details, COVID vaccination details, COVID infection history, risk factors, and severity of illness. Statistical analysis: Data has been summarized using frequency and percentage. Results: Among 215 fully vaccinated medical students, 57 (26%) breakthrough cases were detected, including 21 males (36%) and 36 females (64%) between the ages of 18 and 23 years. Among these, 9 (16%) had received Covaxin and 47 (84%) had received Covishield. The major risk factor for breakthrough infection was close contact with confirmed cases. Among symptomatic students, the majority had only mild symptoms. The predominant symptoms in infected cases were fever, cough, body ache, and sore throat. The majority (51.8%) had their symptoms resolved within 1 week. Conclusion: Identifying the occurrence, severity, and factors responsible for breakthrough infections with SARS-CoV-2 is important, as it may inform the choice of response by healthcare authorities. Asymptomatic cases of breakthrough infections may pose a threat to vulnerable populations.

Candida auris, a multidrug-resistant yeast, is an opportunistic pathogen that is capable of causing invasive infections, particularly in hospitalized patients with compromised immune systems. Whole genome sequencing (WGS) analysis provides valuable information related to the presence of C. auris clades and antifungal drug resistance mutations, and the data can be used to study transmission patterns in healthcare settings. However, analyzing data can be challenging due to its massive size and complexity. The data generated from WGS require advanced computational infrastructure and expertise in bioinformatics to handle tasks such as data preprocessing, quality control, read alignment, and variant calling. The purpose of this review is to provide a comprehensive overview of the computational tools and software used for WGS data analysis of C. auris. In this review, we have summarized all the tools, software, and databases used so far to the best of our knowledge for analysis of C. auris WGS data by several scientists.

Conidiobolomycosis, a rare chronic subcutaneous mycosis, is caused by filamentous fungi belonging to the phylum Entomophthoromycota. The most common form of conidiobolomycosis is the rhinofacial form involving sinuses, nasal passages, and the surrounding tissue. However, rare forms of invasive infection can occur in immunocompromised hosts. Here, we report a case of pulmonary conidiobolomycosis due to Conidiobolus coronatus in a patient with crescentic immunoglobulin A (IgA) nephropathy.

Background: Arboviruses are arthropod-borne viruses transmitted during the blood meal of the arthropod. These arboviruses are considered to be emerging and reemerging infections. Aims and objectives: This survey is being conducted to determine the testing capacity of various hospitals and laboratories for arboviral infections, their testing methods, and positivity rate. Materials and methods: This questionnaire-based study was conducted after obtaining ethical clearance. The questionnaire was circulated via email, WhatsApp, or other electronic modes to clinical microbiologists in India. Data were collected on testing for dengue, chikungunya, Japanese encephalitis (JE), Kyasanur forest disease (KFD), Zika, and West Nile virus from June 2022 to May 2023 (1 year). The collected data were tabulated and analyzed using frequency and percentages. Results: A total of 39 testing facilities responded to the questionnaire. Among these facilities, 20 (51.28%) were from Kerala, and 26 (66.6%) were teaching hospitals, of which 15 (38.46%) were private. Two (5.1%) were stand-alone private laboratories. Rapid diagnostic tests (RDTs), immunoglobulin M (IgM) enzyme-linked immunosorbent assay (ELISA), and reverse transcription polymerase chain reaction (RT-PCR) for ribonucleic acid (RNA) detection were the common tests performed. A total of 1,07,535 samples were tested for the six major arboviral infections, with dengue accounting for 93.59% of the tests conducted. All these diseases are reportable under the Integrated Disease Surveillance Programme (IDSP). Facility for viral culture and isolation, considered the gold standard for diagnosing viral diseases, was not available at any of the centers. Conclusion: This survey is the first of its kind to examine arboviral disease testing capacity across 39 diagnostic facilities in India. Dengue diagnosis was the most common among the arboviral diseases tested. However, paradoxically, tests for potentially fatal viral infections, like Japanese encephalitis virus (JEV), and IgM ELISA for KFD, are only available at referral centers. This study highlights the need for improved capacity building for arboviral disease detection across the country. Early diagnosis is crucial for controlling the spread of these viruses in communities.