StaBle-ABPpred: a stacked ensemble predictor based on biLSTM and attention mechanism for accelerated discovery of antibacterial peptides.

Due to the rapid emergence of multi-drug resistant (MDR) bacteria, existing antibiotics are becoming ineffective. So, researchers are looking for alternatives in the form of antibacterial peptides (ABPs) based medicines. The discovery of novel ABPs using wet-lab experiments is time-consuming and expensive. Many machine learning models have been proposed to search for new ABPs, but there is still scope to develop a robust model that has high accuracy and precision. In this work, we present StaBle-ABPpred, a stacked ensemble technique-based deep learning classifier that uses bidirectional long-short term memory (biLSTM) and attention mechanism at base-level and an ensemble of random forest, gradient boosting and logistic regression at meta-level to classify peptides as antibacterial or otherwise. The performance of our model has been compared with several state-of-the-art classifiers, and results were subjected to analysis of variance (ANOVA) test and its post hoc analysis, which proves that our model performs better than existing classifiers. Furthermore, a web app has been developed and deployed at https://stable-abppred.anvil.app to identify novel ABPs in protein sequences. Using this app, we identified novel ABPs in all the proteins of the Streptococcus phage T12 genome. These ABPs have shown amino acid similarities with experimentally tested antimicrobial peptides (AMPs) of other organisms. Hence, they could be chemically synthesized and experimentally validated for their activity against different bacteria. The model and app developed in this work can be further utilized to explore the protein diversity for identifying novel ABPs with broad-spectrum activity, especially against MDR bacterial pathogens.

Deep-AFPpred: identifying novel antifungal peptides using pretrained embeddings from seq2vec with 1DCNN-BiLSTM.

Fungal infections or mycosis cause a wide range of diseases in humans and animals. The incidences of community acquired; nosocomial fungal infections have increased dramatically after the emergence of COVID-19 pandemic. The increase in number of patients with immunodeficiency / immunosuppression related diseases, resistance to existing antifungal compounds and availability of limited therapeutic options has triggered the search for alternative antifungal molecules. In this direction, antifungal peptides (AFPs) have received a lot of interest as an alternative to currently available antifungal drugs. Although the AFPs are produced by diverse population of living organisms, identifying effective AFPs from natural sources is time-consuming and expensive. Therefore, there is a need to develop a robust in silico model capable of identifying novel AFPs in protein sequences. In this paper, we propose Deep-AFPpred, a deep learning classifier that can identify AFPs in protein sequences. We developed Deep-AFPpred using the concept of transfer learning with 1DCNN-BiLSTM deep learning algorithm. The findings reveal that Deep-AFPpred beats other state-of-the-art AFP classifiers by a wide margin and achieved approximately 96% and 94% precision on validation and test data, respectively. Based on the proposed approach, an online prediction server is created and made publicly available at https://afppred.anvil.app/. Using this server, one can identify novel AFPs in protein sequences and the results are provided as a report that includes predicted peptides, their physicochemical properties and motifs. By utilizing this model, we identified AFPs in different proteins, which can be chemically synthesized in lab and experimentally validated for their antifungal activity.

Accelerating the discovery of antifungal peptides using deep temporal convolutional networks.

The application of machine intelligence in biological sciences has led to the development of several automated tools, thus enabling rapid drug discovery. Adding to this development is the ongoing COVID-19 pandemic, due to which researchers working in the field of artificial intelligence have acquired an active interest in finding machine learning-guided solutions for diseases like mucormycosis, which has emerged as an important post-COVID-19 fungal complication, especially in immunocompromised patients. On these lines, we have proposed a temporal convolutional network-based binary classification approach to discover new antifungal molecules in the proteome of plants and animals to accelerate the development of antifungal medications. Although these biomolecules, known as antifungal peptides (AFPs), are part of an organism's intrinsic host defense mechanism, their identification and discovery by traditional biochemical procedures is arduous. Also, the absence of a large dataset on AFPs is also a considerable impediment in building a robust automated classifier. To this end, we have employed the transfer learning technique to pre-train our model on antibacterial peptides. Subsequently, we have built a classifier that predicts AFPs with accuracy and precision of 94%. Our classifier outperforms several state-of-the-art models by a considerable margin. The results of its performance were proven as statistically significant using the Kruskal-Wallis H test, followed by a post hoc analysis performed using the Tukey honestly significant difference (HSD) test. Furthermore, we identified potent AFPs in representative animal (Histatin) and plant (Snakin) proteins using our model. We also built and deployed a web app that is freely available at https://tcn-afppred.anvil.app/ for the identification of AFPs in protein sequences.

Patient and Health Care Professional Perceptions of the Experience and Impact of Symptoms of Moderate-to-Severe Crohn's Disease in US and Europe: Results from the Cross-Sectional CONFIDE Study.

BACKGROUND: Crohn's disease (CD) significantly affects patients' health-related quality of life and well-being. AIMS: Communicating Needs and Features of IBD Experiences (CONFIDE) survey explores the experience and impact of moderate-to-severe CD symptoms on patients' lives and identifies communication gaps between patients and health care professionals (HCPs). METHODS: Online, quantitative, cross-sectional surveys of patients, and HCPs were conducted in the United States (US), Europe (France, Germany, Italy, Spain, United Kingdom), and Japan. Criteria based on previous treatment, steroid use, and/or hospitalization defined moderate-to-severe CD. US and Europe data are presented as descriptive statistics. RESULTS: Surveys were completed by 215 US and 547 European patients and 200 US and 503 European HCPs. In both patient groups, top three symptoms currently (past month) experienced were diarrhea, bowel urgency, and increased stool frequency, with more than one-third patients wearing diaper/pad/protection at least once a week in past 3 months due to fear of bowel urgency-related accidents. HCPs ranked diarrhea, blood in stool, and increased stool frequency as the most common symptoms. Although 34.0% US and 27.2% European HCPs ranked bowel urgency among the top five symptoms affecting patient lives, only 12.0% US and 10.9% European HCPs ranked it among top three most impactful symptoms on treatment decisions. CONCLUSION: Bowel urgency is common and impactful among patients with CD in the US and Europe. Differences in patient and HCP perceptions of experiences and impacts of bowel urgency exist, with HCPs underestimating its burden. Proactive communication between HCPs and patients in clinical settings is crucial for improving health outcomes in patients with CD.

In vitro assessment of newer colistin-sparing antimicrobial agents for clinical isolates of carbapenem-resistant organisms.

OBJECTIVES: Carbapenem-resistant organisms (CROs) are a significant public health threat globally, particularly in countries like India with high antibiotic resistance rates. The current study investigates the prevalence of CROs, detects resistance mechanisms using phenotypic methods and assesses the efficacy of newer antibiotics against CROs. METHODS: A prospective study conducted at a tertiary care hospital in India during 2021-23. Clinical specimens were processed and bacterial identification was performed using MALDI-TOF mass spectrometry followed by antimicrobial susceptibility testing using CLSI guidelines against a plethora of newer antibiotics for CROs. Carbapenemase production was detected using phenotypic methods, and the presence of the mcr-1 gene was assessed by real-time PCR. RESULTS: During the study period, predominantly (70 %) Gram-negative bacteria were isolated; amongst which 5692 strains were carbapenem-resistant, wherein resistance to different carbapenems ranged from 34.1% to 79 %. Majority of the carbapenemase producers were metallo-ß-lactamases (MBL) producers (75 %). Colistin resistance was noted in 5.4 % of selected carbapenem-resistant isolates. Among newer antibiotics, cefiderocol demonstrated the lowest resistance rates (0-14 %), while resistance to newer ß-lactam/ß-lactamase inhibitor combinations was very high in carbapenem-resistant isolates. Fosfomycin, minocycline and tigecycline, each showing variable efficacy depending on the site of infection. Moreover, newer ß-lactam/ß-lactamase inhibitor combinations offer restricted benefits due to widespread prevalence of MBL in the region. CONCLUSION: The escalating prevalence of CROs in India underscores the urgency for alternative treatment options beyond colistin. Hence, highlighting the critical importance of developing effective strategies to combat carbapenem resistance.

Deep-ABPpred: identifying antibacterial peptides in protein sequences using bidirectional LSTM with word2vec.

The overuse of antibiotics has led to emergence of antimicrobial resistance, and as a result, antibacterial peptides (ABPs) are receiving significant attention as an alternative. Identification of effective ABPs in lab from natural sources is a cost-intensive and time-consuming process. Therefore, there is a need for the development of in silico models, which can identify novel ABPs in protein sequences for chemical synthesis and testing. In this study, we propose a deep learning classifier named Deep-ABPpred that can identify ABPs in protein sequences. We developed Deep-ABPpred using bidirectional long short-term memory algorithm with amino acid level features from word2vec. The results show that Deep-ABPpred outperforms other state-of-the-art ABP classifiers on both test and independent datasets. Our proposed model achieved the precision of approximately 97 and 94% on test dataset and independent dataset, respectively. The high precision suggests applicability of Deep-ABPpred in proposing novel ABPs for synthesis and experimentation. By utilizing Deep-ABPpred, we identified ABPs in the tail protein sequences of Streptococcus bacteriophages, chemically synthesized identified peptides in lab and tested their activity in vitro. These ABPs showed potent antibacterial activity against selected Gram-positive and Gram-negative bacteria, which confirms the capability of Deep-ABPpred in identifying novel ABPs in protein sequences. Based on the proposed approach, an online prediction server is also developed, which is freely accessible at https://abppred.anvil.app/. This web server takes the protein sequence as input and provides ABPs with high probability (>0.95) as output.

AniAMPpred: artificial intelligence guided discovery of novel antimicrobial peptides in animal kingdom.

With advancements in genomics, there has been substantial reduction in the cost and time of genome sequencing and has resulted in lot of data in genome databases. Antimicrobial host defense proteins provide protection against invading microbes. But confirming the antimicrobial function of host proteins by wet-lab experiments is expensive and time consuming. Therefore, there is a need to develop an in silico tool to identify the antimicrobial function of proteins. In the current study, we developed a model AniAMPpred by considering all the available antimicrobial peptides (AMPs) of length $\in $[10 200] from the animal kingdom. The model utilizes a support vector machine algorithm with deep learning-based features and identifies probable antimicrobial proteins (PAPs) in the genome of animals. The results show that our proposed model outperforms other state-of-the-art classifiers, has very high confidence in its predictions, is not biased and can classify both AMPs and non-AMPs for a diverse peptide length with high accuracy. By utilizing AniAMPpred, we identified 436 PAPs in the genome of Helobdella robusta. To further confirm the functional activity of PAPs, we performed BLAST analysis against known AMPs. On detailed analysis of five selected PAPs, we could observe their similarity with antimicrobial proteins of several animal species. Thus, our proposed model can help the researchers identify PAPs in the genome of animals and provide insight into the functional identity of different proteins. An online prediction server is also developed based on the proposed approach, which is freely accessible at https://aniamppred.anvil.app/.

Comparative Diagnostic of Cervical Tuberculous Lymphadenitis: PCR is a Fast, Efficient, and Improved Diagnostic Approach.

Methods: The study included 100 clinically suspected cases of TBLN. Fine needle aspirate (FNA) samples were processed for cytology staining and cultured on LJ & BACTEC 12B media. The biochemical tests were performed to identify the isolates at the species level. Additionally, for PCR, DNA was extracted and used for the diagnosis and identification of mycobacterial species. Results: Patients ranged from 2 to 45 years with a mean age of 24.96 ± 9.10 years. Out of 100 patients, 73% had clinical symptoms of weight loss, followed by fever (72%), anorexia (66%), and night sweats (58%). 24% of patients were found to be smear-positive after Ziehl-Neelsen (ZN) staining and statistically highly significant with PCR. On LJ medium 34% and on BACTEC radiometric 45% of samples were smearing positive. Overall, 48% of cases were PCR-positive for TBLN. When compared with culture, the sensitivity and specificity of PCR were 93.75% and 100%, respectively, which are higher than cytology. The true positive predictive value (PPV) and negative predictive value (NPV) were 83.3% and 61.5%, respectively. Conclusion: This study suggests that PCR is a rapid, sensitive, and specific tool for correct diagnosis of TBLN cases as compared to staining and culture which lead to the early and proper management of mycobacterial diseases.

Sensitivity of liquid-based cytology in the diagnosis of mucormycosis in COVID-19 treated patients.

BACKGROUND: The coronavirus disease 2019 (COVID-19) infection caused by the novel severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) is associated with a wide range of disease patterns, ranging from mild to life-threatening pneumonia. COVID-19 can be associated with a suppressed immune response and/or hyperinflammatory state due to cytokine storm. Reduced immunity, combined with steroid usage to prevent cytokine storm along with various pre-existing co morbidities can prove to be a fertile ground for various secondary bacterial and fungal infection, including mucormycosis. Diagnosis of mucor is a challenging task given high negativity rate of various detection methods. While histopathology is considered the gold standard, the acquisition of necessary tissue biopsy specimens requires invasive procedures and is time consuming. METHOD: In this study various methods of mucor detection, like conventional cytopathology (CCP), liquid-based cytology (LBC, BD SurepathTM ), potassium hydroxide mount (KOH) preparation, culture and histopathology were analysed. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for various methods. RESULTS: This study showed that LBC has sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 72.4%,100%,100% and 38.4% respectively. CONCLUSION: This study showed that, liquid-based cytology (LBC) can be a rapid and effective alternative to histopathology in mucor diagnosis.

COVID associated mucormycosis: A preliminary study from a dedicated COVID Hospital in Delhi.

BACKGROUND: It is an incontrovertible fact that the Rhino Orbital Cerebral Mucormycosis (ROCM) upsurge is being seen in the context of COVID-19 in India. Briefly presented is evidence that in patients with uncontrolled diabetes, a dysfunctional immune system due to SARS-COV-2 and injudicious use of corticosteroids may be largely responsible for this malady. OBJECTIVE: To find the possible impact of COVID 19 infection and various co-morbidities on occurrence of ROCM and demonstrate the outcome based on medical and surgical interventions. METHODOLOGY: Prospective longitudinal study included patients diagnosed with acute invasive fungal rhinosinusitis after a recent COVID-19 infection. Diagnostic nasal endoscopy (DNE) was performed on each patient and swabs were taken and sent for fungal KOH staining and microscopy. Medical management included Injection Liposomal Amphotericin B, Posaconazole and Voriconazole. Surgical treatment was restricted to patients with RT PCR negative results for COVID-19. Endoscopic, open, and combined approaches were utilized to eradicate infection. Follow-up for survived patients was maintained regularly for the first postoperative month. RESULTS: Out of total 131 patients, 111 patients had prior history of SARS COVID 19 infection, confirmed with a positive RT-PCR report and the rest 20 patients had no such history. Steroids were received as a part of treatment in 67 patients infected with COVID 19. Among 131 patients, 124 recovered, 1 worsened and 6 died. Out of 101 known diabetics, 98 recovered and 3 had fatal outcomes. 7 patients with previous history of COVID infection did not have any evidence of Diabetes mellitus, steroid intake or any other comorbidity. CONCLUSION: It can be concluded that ROCM upsurge seen in the context of COVID-19 in India was mainly seen in patients with uncontrolled diabetes, a dysfunctional immune system due to SARS-COV-2 infection and injudicious use of corticosteroids.

Morbidity and Mortality of Necrotizing Fasciitis and Their Prognostic Factors in Children.

Background: This is a prospective study of the clinico-etiologic profile and factors affecting outcomes in 40 children managed for necrotizing fasciitis (NF). Materials and Methods: Demographic details, clinical characteristics, and laboratory parameters were recorded, and the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score was calculated. Primary outcome (survival vs. nonsurvival) was noted, and prognostic factors were identified. Results: Initiating factors included boils (45%), i.v. cannula extravasations (22.5%), and blunt trauma (17.5%). Lesion (s) were predominantly on the lower limbs (35%) and trunk (25%). Twenty-two patients (55%) had <5% body surface area (BSA) involved. Severely deranged clinical and laboratory parameters were common. Ultrasound localized fluid collections. Pus cultures showed methicillin-resistant Staphylococcus aureus (52.5%), methicillin-sensitive S. aureus [27.5%], and polymicrobial growth (20%). Blood culture was positive in 24 patients (60%). Most isolates were sensitive to clindamycin and amoxy-clavulanate. Prognostic factors for mortality (n = 6; 15%) included categorization as "Sick," BSA involvement >10%, thrombocytopenia, raised serum creatinine, late debridement, and polymicrobial blood culture isolates. All six nonsurvivors had a LRINEC score of ≥8 and positive blood cultures. Six patients (20.7%) developed unsightly scars and 5 (17.24%) contractures across joints. Conclusions: Pediatric NF has significant morbidity and mortality. Patients with adverse prognostic factors can benefit from early referral to a facility with a critical care unit. Adequate wound management is essential to minimize residual deformity.

Evidence of the presence of SARS-CoV-2 virus in atmospheric air and surfaces of a dedicated COVID hospital.

The present study was conducted from July 1, 2020 to September 25, 2020 in a dedicated coronavirus disease 2019 (COVID-19) hospital in Delhi, India to provide evidence for the presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in atmospheric air and surfaces of the hospital wards. Swabs from hospital surfaces (patient's bed, ward floor, and nursing stations area) and suspended particulate matter in ambient air were collected by a portable air sampler from the medicine ward, intensive care unit, and emergency ward admitting COVID-19 patients. By performing reverse-transcriptase polymerase chain reaction (RT-PCR) for E-gene and RdRp gene, SARS-CoV-2 virus was detected from hospital surfaces and particulate matters from the ambient air of various wards collected at 1 and 3-m distance from active COVID-19 patients. The presence of the virus in the air beyond a 1-m distance from the patients and surfaces of the hospital indicates that the SARS-CoV-2 virus has the potential to be transmitted by airborne and surface routes from COVID-19 patients to health-care workers working in COVID-19 dedicated hospital. This warrants that precautions against airborne and surface transmission of COVID-19 in the community should be taken when markets, industries, educational institutions, and so on, reopen for normal activities.

Clinical characteristic and epidemiological features of SARS CoV -2 disease patients from a COVID 19 designated Hospital in New Delhi.

SARS CoV -2 infection is rapidly evolving as a serious global pandemic. The present study describes the clinical characteristics of SARS CoV-2 infection patients. The Samples were subjected to RT - PCR or Rapid Antigen test for diagnosis of SARS CoV- 2. A cohort of 3745 patients with confirmed diagnosis of SARS CoV -2 infection in a tertiary care center in New Delhi, India were included in this study. Data was collected from offline and online medical records over a period of six months. Amongst 3745 SARS CoV -2 infected patients, 2245 (60%) were symptomatic and 1500 (40%) were asymptomatic. Most common presenting symptom was cough (49.3%) followed febrile episodes (47.1%), breathlessness (42.7%) and sore throat (35.1%). Cough along with breathlessness (24.1) was the most common combination of symptoms followed by fever with cough (22.7). The most common comorbidity found among symptomatic group was diabetes (42.5%) followed by hypertension (21.4%) and chronic kidney disease (18%). Comorbidities like diabetes mellitus, chronic diseases of lungs, heart and kidneys were found to be common in symptomatic group and this was found to be statistically significant (p<0.05). COVID-19 is an evolving disease and data from our study help in understanding the clinic-epidemiological profile of patients. This article is protected by copyright. All rights reserved.

Evaluation of SARS-CoV-2 in Tears of Patients with Moderate to Severe COVID-19.

PURPOSE: To investigate the presence of SARS-CoV-2 RNA in tears of patients with moderate to severe coronavirus disease 2019 (COVID-19). DESIGN: Cross-sectional study. PARTICIPANTS: Patients with laboratory-proven moderate to severe COVID-19. METHODS: Tears were collected within 48 hours of laboratory confirmation using 3 methods: conjunctival swab plus Schirmer's test strips (group 1), conjunctival swab (group 2), and Schirmer's test strips (group 3). Samples from both the eyes of each patient were transported in a single viral transport media for real-time RT-PCR. Detailed demographic profiles, systemic symptoms, comorbidities, and ocular manifestations were noted. MAIN OUTCOME MEASURES: Viral load of a sample was determined using cycle threshold (Ct) value of E gene. A specimen was considered to show positive results if the amplification curve for the E gene crossed the threshold line within 35 cycles and if it showed positive results on an RNA-dependent RNA polymerase or open reading frame 1b gene assay. RESULTS: Of the 78 patients enrolled in the study, samples from 3 patients were found to be inadequate for analysis. Thirty-six patients (48%) had moderate disease, whereas 39 patients (52%) had severe disease, with no ocular involvement in any patient. In the 75 patients, RT-PCR analysis of tears showed positive results in 18 patients (24%), and 29 of 225 samples (12.9%) showed positive results. Positive results were found in 11 (14.7%), 11 (14.7%), and 7 (9.3%) patients in groups 1, 2, and 3, respectively (P = 0.3105). Mean Ct values in groups 1, 2, and 3 were 28.36 ± 6.15, 29.00 ± 5.58, and 27.86 ± 6.46 (P = 0.92), respectively. Five patients showed positive RT-PCR results by all 3 methods (mean Ct value, 25.24 ± 6.33), and 12 patients showed positive results by any of the 3 methods (mean Ct value, 32.16 ± 1.94), the difference in Ct values being statistically significant (P = 0.029). The median value of symptomatology in patients with positive RT-PCR results from tears was 5 days (range, 4-9 days). CONCLUSIONS: SARS-CoV-2 RNA was detected in tears of 24% of patients with laboratory-proven moderate to severe COVID-19. Conjunctival swab remains the gold standard of tear collection for RT-PCR assay. A significantly higher possibility of viral transmission exists through tears in patients with moderate to severe COVID-19.

Functional Analysis of DNMT1 SNPs (rs2228611 and rs2114724) Associated with Schizophrenia.

A recent study showed the association of minor alleles of rs2228611 (T allele) and rs2114724 (T allele) of DNMT1 with schizophrenia (SZ) and suggested their effects on splicing of the transcripts. We performed a replication study using 310 controls and 304 SZ patients and confirmed the association of the homozygous minor allele genotypes with SZ (P = 0.04 for rs2114724 and P = 0.007 for rs2228611). This significant association persisted after Bonferroni correction when the previously published data of 301 controls and 325 patients were also considered (P ≤ 0.0002). In addition, we found that the proportion of male patients with homozygous minor alleles at rs2114724 was significantly higher than that of females (P = 0.002). When haplotype analysis of both loci was performed, we observed a significant association of T/T-T/T and T/T-C/T (P = 0.04) haplotypes with SZ. To gain insights into the functional effects of the two SNPs on the levels of DNMT1 transcripts, quantitative real-time PCR experiments were performed using peripheral blood monocytes from 10 individuals each with T/T-T/T (homozygous minor allele), C/T-C/T (heterozygous), and C/C-C/C (homozygous major allele) haplotypes. Independently, the levels of DNMT1 protein were also compared in three individuals each by immunofluorescence. These results suggest that neither DNMT1 transcript nor the protein levels were significantly different in the peripheral blood monocytes among the individuals studied for the three groups. Taken together, our results confirm that the two minor alleles in homozygosity are associated with SZ but with no discernible effects on transcript or protein levels of DNMT1 in the peripheral blood monocytes of the small number of samples tested.

Decellularization of Skin Tissue.

Biomaterials science encompasses elements of medicine, biology, chemistry, materials, and tissue engineering. They are engineered to interact with biological systems to treat, augment, repair, or replace lost tissue function. The choice of biomaterial depends on the procedure being performed, the severity of the patient's condition, and the surgeon's preference. Prostheses made from natural-derived biomaterials are often derived from decellularized extracellular matrix (ECM) of animal (xenograft) or human (allograft) origin. Advantages of using ECM include their resemblance in morphology and three-dimensional structures with that of tissue to be replaced. Due to this, scientists all over are now focusing on naturally derived biomaterials which have been shown to possess several advantages compared to synthetic ones, owing to their biocompatibility, biodegradability, and remodeling properties. Advantages of a naturally derived biomaterial enhance their application for replacement or restoration of damaged organs/tissues. They adequately support cell adhesion, migration, proliferation, and differentiation. Naturally derived biomaterials can induce extracellular matrix formation and tissue repair when implanted into a defect by enhancing attachment and migration of cells from surrounding environment. In the current chapter, we will focus on the natural and synthetic dermal matrix development and all of the progress in this field.

Neuropathology mediated through caspase dependent extrinsic pathway in goat kids naturally infected with PPRV.

Peste des petits ruminant (PPR), a highly contagious viral disease of small ruminants, is characterized by erosive stomatitis and pneumo-enteritis. However, its neurovirulence potential as observed with other morbilliviruses has not been fully investigated. The present study describes the neuropathological alterations induced by PPR virus through apoptotic pathway. A total number of 12 carcasses of local breed goat kids of either sex were received for postmortem examination. The clinical history was described as symptoms of mucopurulent nasal discharge, high to low grade fever, erosive stomatitis, dyspnoea and profuse watery diarrhoea followed by mortality of 35 goat kids within a week. The pathoanatomical lesions and immunohistochemical demonstration of PPRV antigen in lungs, intestine, spleen and lymph nodes confirmed PPR disease in goats. Grossly, five brain specimens showed moderate to severe leptomeningeal congestion during necropsy. Microscopically, brain sections showed leptomeningitis and nonsuppurative encephalitis characterized by vascular congestion, haemorrhages in the parenchyma, perivascular cuffing with mild to moderate mononuclear cells (mainly lymphocytes and few macrophages), focal to diffuse microgliosis, neuronal degeneration, satellitosis and neuronophagia. Immunolabelling of viral antigen was observed in the cytoplasm of neurons and glial cells. The RT-PCR amplification of N gene fragment also confirmed the presence of PPRV in the brain. The strong immunoreactivity of Caspase-3, Caspase-8 and comparatively lower expression of caspase-9 along with the absence of any reactivity for Apaf-1 antigen in the brain sections indicated the role of caspase dependent extrinsic pathway in inducing neuropathological changes. The presence of apoptotic neurons in the brain by TUNEL assay further confirmed the apoptosis and strong immunoreactivity of iNOS in neurons which suggested the generation of oxidative stress, that might have induced the apoptosis. The overall findings confirm the neurovirulence potential of PPR virus, via the extrinsic pathway of apoptosis, in natural cases of PPR disease in goat kids.

Analysis of 15q11.2 CNVs in an Indian population with schizophrenia.

Copy number variants (CNVs) of 15q11.2 yielded conflicting reports on their association with schizophrenia (SZ), indicating the need for replication studies. Because there are no 15q11.2 CNV studies on Indian patients, we began by testing 307 SZ patients and 359 age- and sex-matched controls from South India. Using an improved multiplex ligation probe amplification, six deletions were found in patients and three in controls (p = 0.31), whereas one duplication was found in patients and three in controls (p = 0.63). Analysis of families of two patients and two controls with deletions indicated that the mutations were de novo. In conclusion, there seems to be no significant difference in the frequencies of 15q11.2 CNVs among the controls and patients studied here. Future studies involving a larger number of controls and patients are expected to provide better clarity on the relationship between 15q11.2 CNVs and SZ patients from India.

Issues in antifungal stewardship: an opportunity that should not be lost.

Many countries have observed an increase in the incidence of invasive fungal infections (IFIs) over the past two decades with emergence of new risk factors and isolation of new fungal pathogens. Early diagnosis and appropriate antifungal treatment remain the cornerstones of successful outcomes. However, due to non-specific clinical presentations and limited availability of rapid diagnostic tests, in more than half of cases antifungal treatment is inappropriate. As a result, the emergence of antifungal resistance both in yeasts and mycelial fungi is becoming increasingly common. The Delhi Chapter of the Indian Association of Medical Microbiologists (IAMM-DC) organized a 1 day workshop in collaboration with BSAC on 10 December 2015 in New Delhi to design a road map towards the development of a robust antifungal stewardship programme in the context of conditions in India. The workshop aimed at developing a road map for optimizing better outcomes in patients with IFIs while minimizing unintended consequences of antifungal use, ultimately leading to reduced healthcare costs and prevention development of resistance to antifungals. The workshop was a conclave of all stakeholders, eminent experts from India and the UK, including clinical microbiologists, critical care specialists and infectious disease physicians. Various issues in managing IFIs were discussed, including epidemiology, diagnostic and therapeutic algorithms in different healthcare settings. At the end of the deliberations, a consensus opinion and key messages were formulated, outlining a step-by-step approach to tackling the growing incidence of IFIs and antifungal resistance, particularly in the Indian scenario.

Convergence of Minds: For Better Patient Outcome in Intensive Care Unit Infections.

BACKGROUND: There is emergence of resistance to the last-line antibiotics such as carbapenems in Intensive Care Units (ICUs), leaving little effective therapeutic options. Since there are no more newer antibiotics in the armamentarium in the near future, it has become imperative that we harness the interdisciplinary knowledge for the best clinical outcome of the patient. AIMS: The aim of the conference was to utilize the synergies between the clinical microbiologists and critical care specialists for better patient care and clinical outcome. MATERIALS AND METHODS: A combined continuing medical education program (CME) under the aegis of the Indian Association of Medical Microbiologists - Delhi Chapter and the Indian Society of Critical Care Medicine, Delhi and national capital region was organized to share their expertise on the various topics covering epidemiology, diagnosis, management, and prevention of hospital-acquired infections in ICUs. RESULTS: It was agreed that synergy between the clinical microbiologists and critical care medicine is required in understanding the scope of laboratory tests, investigative pathway testing, hospital epidemiology, and optimum use of antibiotics. A consensus on the use of rapid diagnostics such as point-of-care tests, matrix-assisted laser desorption ionization-time of flight mass spectrometry, and molecular tests for the early diagnosis of infectious disease was made. It was agreed that stewardship activities along with hospital infection control practices should be further strengthened for better utilization of the antibiotics. Through this CME, we identified the barriers and actionables for appropriate antimicrobial usage in Indian ICUs. CONCLUSIONS: A close coordination between clinical microbiology and critical care medicine opens up avenues to improve antimicrobial prescription practices.