Search

Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Enterobacter species represent widely distributed opportunistic pathogens, commonly associated with plants and humans. In the present study, we performed a detailed molecular characterization as well as genomic study of a type VI secretion system (T6SS) bacterium belonging to member of the family Enterobacteriaceae and named Enterobacter sp. S-33. The comparative sequence analysis of the 16S rRNA gene showed that the strain was closely related to other Enterobacter species. The complete genome of the strain with a genome size of 4.6 Mbp and GC-content of 55.63% was obtained through high-quality sequencing. The genomic analysis with online tools unravelled the various genes belonging to the bacterial secretion system, antibiotic resistance, virulence, efflux pumps, etc. The isolate showed the motility behavior that contributes to Enterobacter persistence in a stressed environment and further supports infections. PCR amplification and further sequencing confirmed the presence of drug-efflux genes acrA, acrB, and outer membrane genes, viz. OmpA, OmpC, and OmpF. The cell surface hydrophobicity and co-aggregation assay against different bacterial strains illustrated its putative pathogenic nature. Genome mining identified various biosynthetic gene clusters (BGCs) corresponding to non-ribosomal proteins (NRPS), siderophore, and arylpolyene production. Briefly, genome sequencing and detailed characterization of environmental Enterobacter isolate will assist in understanding the epidemiology of Enterobacter species, and the further prevention and treatment of infectious diseases caused by these broad-host range species., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Podocyte infolding glomerulopathy (PIG) is a rare pathological entity, diagnosed by electron microscopic demonstration of diffuse infolding of the podocytes into the glomerular basement membranes. We report the first case from United Kingdom exhibiting typical ultrastructural features of PIG in a male with Type II diabetes mellitus, hypertension and common variable immune deficiency. Renal biopsy revealed phospholipase A2 receptor (PLA2R) immunostain positive membranous nephropathy (MN) but no serum PLA2R antibodies. Diffuse infolding of the podocytes into the glomerular basement membranes along with pathognomonic microspherular and microtubular intra basement membrane clusters distributed diffusely and globally were noted on electron microscopy, diagnostic of PIG. We postulate a shared pathomechanistic link between PIG and MN, highlighting the overlapping features of both conditions., Competing Interests: There are no conflicts of interest., (© 2024 Indian Journal of Nephrology | Published by Scientific Scholar.)

Oral cancer ranks as the sixth most prevalent form of cancer worldwide, presenting a significant public health concern. According to the World Health Organization (WHO), within a 5-year period following diagnosis, the mortality rate among oral cancer patients of all stages stands at 45%. In this study, a total of 60 patients divided into 2 groups were recruited. Group A included 30 histo-pathologically confirmed OSCC patients and Group B included 30 healthy controls. A standardized procedure was followed to collect saliva samples. FTIR spectroscopy was done for all the saliva samples collected from both Group A and B. An IR Prestige-21 (Shimadzu Corp, Japan) spectrometer was used to record IR spectra in the 40-4000 cm -1 range SVM classifier was applied in the classification of disease state from normal subjects using FTIR data. The peaks were identified at wave no 1180 cm -1 , 1230 cm -1 , 1340 cm -1 , 1360 cm -1 , 1420 cm -1 , 1460 cm -1 , 1500 cm -1 , 1540 cm -1 , 1560 cm -1 , and 1637 cm -1 . The observed results of SVM demonstrated the accuracy of 91.66% in the classification of Cancer tissues from the normal subjects with sensitivity of 83.33% while specificity and precision of 100.0%. The development of oral cancer leads to noticeable alterations in the secondary structure of proteins. These findings emphasize the promising use of ATR-FTIR platforms in conjunction with machine learning as a reliable, non-invasive, reagent-free, and highly sensitive method for screening and monitoring individuals with oral cancer., Competing Interests: Conflict of interestThe authors have no conflict of interest regarding the publication of this article., (© Association of Otolaryngologists of India 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Background and Aim: The regular uptake of a high-fat diet (HFD) with changing lifestyle causes atherosclerosis leading to cardiovascular diseases and autonomic dysfunction. Therefore, the current study aimed to investigate the correlation of autonomic activity to lipid and atherosclerosis markers. Further, the study proposes a support vector machine (SVM) based model in the prediction of atherosclerosis severity., Methods and Results: The Lead-II electrocardiogram and blood markers were measured from both the control and the experiment subjects each week for nine consecutive weeks. The time-domain heart rate variability (HRV) parameters were derived, and the significance level was tested using a one-way Analysis of Variance. The correlation analysis was performed to determine the relation between autonomic parameters and lipid and atherosclerosis markers. The statistically significant time-domain values were used as features of the SVM. The observed results demonstrated the reduced time domain HRV parameters with the increase in lipid and atherosclerosis index markers with the progressive atherosclerosis severity. The correlation analysis revealed a negative association between time-domain HRV parameters with lipid and atherosclerosis parameters. The percentage accuracy increases from 86.58% to 98.71% with the increase in atherosclerosis severity with regular consumption of HFD., Conclusions: Atherosclerosis causes autonomic dysfunction with reduced HRV. The negative correlation between autonomic parameters and lipid profile and atherosclerosis indexes marker revealed the potential role of vagal activity in the prognosis of atherosclerosis progression. The support vector machine presented a respectable accuracy in the prediction of atherosclerosis severity from the control group., Competing Interests: Declaration of competing interest Authors declare that they have no conflict of interest., (Copyright © 2024 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Low-grade gliomas (LGGs) are a heterogeneous group of tumors with an average 10-year survival rate of 40%-55%. Current treatment options include chemotherapy, radiotherapy, and gross total resection (GTR) of the tumor. The extent of resection (EOR) plays an important role in improving surgical outcomes. However, the major obstacle in treating low-grade gliomas is their diffused nature and the presence of residual cancer cells at the tumor margins post resection. Cold Atmospheric Plasma (CAP) has shown to be effective in targeted killing of tumor cells in various glioma cell lines without affecting non-tumor cells through Reactive Oxygen and Nitrogen Species (RONS). However, no study on the effectiveness of CAP has been carried out in LGG tissues till date. In this study, we applied helium-based CAP on tumor tissues resected from LGG patients. Our results show that CAP is effective in promoting RONS accumulation in LGG tissues when CAP jet parameters are set at 4 kV voltage, 5 min treatment time and 3 lpm gas flow rate. We also observed that CAP jet is more effective in thinner slice preparations of tumor as compared to thick tumor samples. Our results indicate that CAP could prove to be an effective adjunct therapy in glioma surgery to target residual cancer cells to improve surgical outcome of patients with low-grade glioma., (© 2024 IOP Publishing Ltd.)

The population and modernization of society have increased dramatically from past few decades. In order to meet societal expectations, there has been a massive industrialization and resource exploitation. Anthropogenic practices like disposal of hazardous waste, large carbon footprint release variety of xenobiotic substances into the environment, which endanger the health of the natural ecosystem. Therefore, discovering proper long-term treatment approaches is a global concern. Various physical and chemical approaches are employed to remove contaminants. However, these technologies possess limitations like high cost and low efficacy. Consequently, bioremediation is regarded as one of the most promising remedies to these problems. It creates the option of either totally removing pollutants or transforming them into nonhazardous compounds with the use of natural biological agents. Several microorganisms are being utilized for bioremediation among which yeasts possess benefits such as high biodegradability, ease of cultivation etc. The yeast of Candida genus has the capability to effectively eliminate heavy metal ions, as well as to degrade and emulsify hydrocarbons which makes it a promising candidate for this purpose. The review highlights many potential uses of Candida in various remediation strategies and discusses future directions for research in this field., (© The Author(s) 2023. Published by Oxford University Press on behalf of Applied Microbiology International.)

For several years now, organic-inorganic hybrid perovskite materials have shown remarkable progress in the field of opto-electronic devices. Herein, we introduce a cathode-side passivation layer of poly(methyl methacrylate) (PMMA) for a highly efficient and stable self-powered CH 3 NH 3 PbI 3 perovskite-based photodiode. For effective noise-current suppression, the PMMA passivation layer was employed between a light-absorbing layer of CH 3 NH 3 PbI 3 (MAPbI 3 ) perovskite and an electron transport layer of [6,6]-phenyl-C61-butyric acid methyl ester. Due to its passivation effect on defects in perovskite film, the PMMA passivation layer can effectively suppress interface recombination and reduce the leakage/noise current. Without external bias, the MAPbI 3 photodiode with the PMMA layer demonstrated a significantly high specific detectivity value (~1.07 × 10 12 Jones) compared to that of a conventional MAPbI 3 photodiode without a PMMA layer. Along with the enhanced specific detectivity, a wide linear dynamic response (~127 dB) with rapid rise (~50 μs) and decay (~17 μs) response times was obtained. Furthermore, highly durable dynamic responses of the PMMA-passivated MAPbI 3 photodiode were observed even after a long storage time of 500 h. The results achieved with the cathode-side PMMA-passivated perovskite photodiodes represent a new means by which to realize highly sensitive and stable self-powered photodiodes for use in developing novel opto-electronic devices.

Organohalide perovskite materials and related optoelectronic applications have drawn significant attention due to their promising high-performance photon-to-electricity conversion efficiencies. Herein, we demonstrate a highly sensitive self-powered perovskite-based photodetector created with a noise-current-suppressible passivation layer of poly(methyl methacrylate) (PMMA) at the interface between a CH 3 NH 3 PbI 3 light-absorbing layer and a NiO x hole-transporting layer. Along with the defect passivation effect, the PMMA layer effectively diminishes unwanted carrier recombination losses at the interface, resulting in a significant reduction of the leakage/noise current. Consequently, without external bias, a remarkably high level of specific detectivity (∼4.5 × 10 13 Jones from the dark current and ∼0.81 × 10 12 Jones from the noise current) can be achieved due to the use of the PMMA passivation layer, greatly exceeding those of conventional unpassivated perovskite devices. Moreover, we observed a very wide linear dynamic response range of ∼129 dB together with rapid rise and decay response times of ∼52 and ∼18 µs, respectively. Overall, these results provide a solid foundation for advanced interface-engineering to realize high-performance self-powered perovskite photodetectors for various optoelectronic applications.

Background : The ongoing drug epidemic in the United States has shown that there are geographic differences in overdose fatalities. This article introduces a new way to study spatial differences in drug-related mortality, by distinguishing the fatalities of residents and visitors to a region. Methods : Using records of United States deaths from 2001 to 2020, this study examined fatal overdoses among residents and visitors to U.S. metropolitan areas. Results : The findings revealed that the drug fatality levels of residents and visitors differed from one another in many cities. These differences were most pronounced in larger metro areas, where the drug mortality of visitors was disproportionately high. Conclusions : Discussion focuses on implications and possible explanations for these findings, as well as their potential connection to classical conditioning of drug tolerance. More generally, comparing the fatalities of residents and visitors may provide a way to tease apart the roles of person-specific and location-specific contributors to overdose risk.

Oral malignant and potentially malignant conditions affect several people worldwide each year. The early diagnoses of these conditions play an important role in prevention and recovery. Vibrational spectroscopy techniques such as Raman spectroscopy (RS) and Fourier-transform infrared (FTIR) spectroscopy are used in the early, non-invasive, label-free diagnosis of malignant and pre-malignant conditions, and are areas of active research. However, there is no conclusive evidence suggesting the translatability of these methods into clinical practice. This systematic review and meta-analysis presents pooled evidence for RS and FTIR methods in the detection of malignant and potentially malignant conditions of the oral cavity. Electronic databases were searched for published literature on RS and FTIR in the diagnosis of oral malignant and potentially malignant conditions. The pooled sensitivity, specificity, diagnostic accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), pre-test, and post-test probability were then calculated using the random-effects model. A subgroup analysis was conducted separately for RS and FTIR methods. A total of 12 studies were included (8 of RS; 4 of FTIR) as per the eligibility criteria. The pooled sensitivity and specificity of the vibrational spectroscopy methods were calculated to be 0.99 (95% confidence interval [CI]: 0.90, 1.00) and 0.94 (95% CI: 0.85, 0.98), respectively. The area under the curve (AUC) for the summary receiving operator characteristic curve was found to be 0.99 (0.98-1.00). Therefore, the results obtained in this study suggest that the RS and FTIR methods offer great potential to be used in the early diagnosis of oral malignant and pre-malignant conditions., Competing Interests: None

The development of novel types of biogenic surface-active compounds is of greater interest for combating many diseases and infections. In this respect research and development of biosurfactant has gained immense importance. Substantially, biosurfactant is defined as a class of active amphiphilic chemical compounds that comprise hydrophobic and hydrophilic moieties on their surfaces. It is generally known that many kinds of microorganisms can be used to produce these surfactants or surface-active compounds. Hosting interesting features such as biodegradability, emulsifying/de-emulsifying capacity, low toxicity, and antimicrobial activities; these amphiphilic compounds in recent years have flourished as an ideal replacement for the chemically synthesized surfactant, and also have various commercial attractions. Both bacteria and fungi are the producers of these amphiphilic molecules; however, the pathogenicity of certain bacterial strains has caused a shift in interest toward fungi. Therefore, various fungi species have been reported for the production of biosurfactants amongst which Candida species have been the most studied strains. Biosurfactants uphold desired properties like antibacterial, antifungal, antiviral, antiadhesion, and anticancer activity which proves them an ideal candidate for the application in various fields like pharmaceutical, gene therapy, medical insertion safety, immunotherapy to fight against many chronic diseases, and so forth. Hence, this review article discusses the pharmaceutical prospects of biosurfactants produced from different fungal species, providing new directions toward the discovery and development of molecules with novel structures and diverse functions for advanced application in the medical field., (© 2022 Wiley-VCH GmbH.)

Enterobacter species are responsible for causing infections of the lower respiratory tract, urinary tract, meninges, etc. Proteins secreted by these species may act as determinants of host-pathogen interaction and play a role in virulence. Among the secreted proteins, the Type VI secretion system (T6SS) acts as a molecular nanomachine to deliver many effector proteins directly into prey cells in a contact-dependent manner. The secreted proteins may provide an idea for the interaction of bacteria to their environment and an understanding of the role of these proteins for their role in bacterial physiology and behaviour. Therefore, aim of this study was to characterize the secreted proteins in the culture supernatant by a T6SS bacterium Enterobacter sp. S-33 using nano-LC-MS/MS tool. Using a combined mass spectrometry and bioinformatics approach, we identified a total of 736 proteins in the secretome. Bioinformatics analysis predicting subcellular localization identified 110 of the secreted proteins possessed signal sequences. By gene ontology analysis, more than 80 proteins of the secretome were classified into biological or molecular functions. More than 20 percent of secretome proteins were virulence proteins including T6SS proteins, proteins involved in adherence and fimbriae formation, molecular chaperones, outer membrane proteins, serine proteases, antimicrobial, biofilm, exotoxins, etc. In summary, the results of the present study of the S-33 secretome provide a basis for understanding the possible pathogenic mechanisms and future investigation by detailed experimental approach will provide a confirmation of secreted virulence proteins in the exact role of virulence using the in vivo model., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Atherosclerosis leads to coronary artery disease (CAD) and myocardial infarction (MI), a major cause of morbidity and mortality worldwide. The computer-aided prognosis of atherosclerotic events with the electrocardiogram (ECG) derived heart rate variability (HRV) can be a robust method in the prognosis of atherosclerosis events., Methods: A total of 70 male subjects aged 55 ± 5 years participated in the study. The lead-II ECG was recorded and sampled at 200 Hz. The tachogram was obtained from the ECG signal and used to extract twenty-five HRV features. The one-way Analysis of variance (ANOVA) test was performed to find the significant differences between the CAD, MI, and control subjects. Features were used in the training and testing of a two-class artificial neural network (ANN) and support vector machine (SVM)., Results: The obtained results revealed depressed HRV under atherosclerosis. Accuracy of 100% was obtained in classifying CAD and MI subjects from the controls using ANN. Accuracy was 99.6% with SVM, and in the classification of CAD from MI subjects using SVM and ANN, 99.3% and 99.0% accuracy was obtained respectively., Conclusions: Depressed HRV has been suggested to be a marker in the identification of atherosclerotic events. The good accuracy observed in classification between control, CAD, and MI subjects, revealed it to be a non-invasive cost-effective approach in the prognosis of atherosclerotic events., Competing Interests: The authors report no conflicts of interest in this work.

We highlight the reported developments of the palladium-catalyzed C-H activation and functionalization of the inactive/unreactive prochiral C(sp 3 )-H bonds of aliphatic and alicyclic compounds. There exist numerous classical methods for generating contiguous stereogenic centers in a compound with a high degree of stereocontrol. Along similar lines, the Pd(II)-catalyzed, directing group-aided functionalization of inactive prochiral/diastereotopic C(sp 3 )-H bonds have been exploited to accomplish the stereoselective construction of stereo-arrays in organic compounds. We present a concise discussion on how specific strategies consisting of Pd(II)-catalyzed, directing group-aided C(sp 3 )-H functionalization have been utilized to generate two or more stereogenic centers in aliphatic and alicyclic compounds.

Diabetes is a very common occurring disease, diagnosed by hyperglycemia. The established mode of diagnosis is the analysis of blood glucose level with the help of a hand-held glucometer. Nowadays, it is also known for affecting multi-organ functions, particularly the microvasculature of the cardiovascular system. In this work, an alternative diagnostic system based on the heart rate variability (HRV) analysis and artificial neural network (ANN) and support vector machine (SVM) have been proposed. The experiment and data recording has been performed on male Wister rats of 10-12 week of age and 200 ± 20 gm of weight. The digital lead-I electrocardiogram (ECG) data are recorded from control (n = 5) and Streptozotocin-induced diabetic rats (n = 5). Nine time-domain linear HRV parameters are computed from 60 s of ECG data epochs and used for the training and testing of backpropagation ANN and SVM. Total 526 (334 Control and 192 diabetics) such datasets are computed for the testing of ANN for the identification of the diabetic conditions. The ANN has been optimized for architecture 9:5:1 (Input: hidden: output neurons, respectively) with the optimized learning rate parameter at 0.02. With this network, a very good classification accuracy of 96.2% is achieved. While similar accuracy of 95.2% is attained using SVM. Owing to the successful implementation of HRV parameters based automated classifiers for diabetic conditions, a non-invasive, ECG based online prognostic system can be developed for accurate and non-invasive prediction of the diabetic condition.

Hybrid organic-inorganic perovskite materials provide noteworthy compact systems that could offer ground-breaking architectures for dynamic operations and advanced engineering in high-performance energy-harvesting optoelectronic devices. Here, we demonstrate a highly effective self-powered perovskite-based photodiode with an electron-blocking hole-transport layer (NiO x ). A high value of responsivity (R = 360 mA W -1 ) with good detectivity (D = 2.1 × 10 11 Jones) and external quantum efficiency (EQE = 76.5%) is achieved due to the excellent interface quality and suppression of the dark current at zero bias voltage owing to the NiO x layer, providing outcomes one order of magnitude higher than values currently in the literature. Meanwhile, the value of R is progressively increased to 428 mA W -1 with D = 3.6 × 10 11 Jones and EQE = 77% at a bias voltage of - 1.0 V. With a diode model, we also attained a high value of the built-in potential with the NiO x layer, which is a direct signature of the improvement of the charge-selecting characteristics of the NiO x layer. We also observed fast rise and decay times of approximately 0.9 and 1.8 ms, respectively, at zero bias voltage. Hence, these astonishing results based on the perovskite active layer together with the charge-selective NiO x layer provide a platform on which to realise high-performance self-powered photodiode as well as energy-harvesting devices in the field of optoelectronics.

Polymeric light-emitting materials have been developed recently as an attractive solution-processable alternative to conventional vacuum-deposited small molecules in organic/polymeric light-emitting diodes, but they are still limited in terms of their performance, especially with low luminance and efficiency. We report on some noteworthy characteristics of a new type of single emitting layer (EML), composed of a blend of a host blue-emitting polyspirobifluorene-based copolymer and a guest yellow-emitting poly(p-phenylene vinylene) derivative copolymer. These host and guest polymers have nearly identical highest occupied molecular orbital levels of about 5.2 eV, and lowest unoccupied molecular orbital levels of about 2.4 eV and 2.9 eV, respectively, minimizing the prevailing charge-trapping properties of their blend. Even in the absence of the charge-trapping effect, it is shown that very bright green electroluminescent (EL) emission with a maximum luminance of ~142,000 cd/m 2 can be realized for the blended host:guest EML at a moderate concentration (~5 wt%) of the guest polymer. Current efficiency is also observed to be up to ~14 cd/A, which is much higher than those (3.6~5.1 cd/A) of reference devices with pure host or pure guest polymeric EMLs. Moreover, there is a small change in green color emission, with CIE coordinates of (0.35, 0.60) even at high luminance, showing good color stability of the EL emission from the blended EML. These significant improvements in device performance are mainly attributed to efficient Förster resonance energy transfer between the host and guest polymers in the blended EML. Together with its simple structure and easy processability, the high brightness and efficiency of our blended polymeric EML provides a new platform for the development of solution-processable light-emitting devices and/or advanced emissive display devices.

The RV144 Phase III clinical trial with ALVAC-HIV prime and AIDSVAX B/E subtypes CRF01_AE (A244) and B (MN) gp120 boost vaccine regime in Thailand provided a foundation for the future development of improved vaccine strategies that may afford protection against the human immunodeficiency virus type 1 (HIV-1). Results from this trial showed that immune responses directed against specific regions V1V2 of the viral envelope (Env) glycoprotein gp120 of HIV-1, were inversely correlated to the risk of HIV-1 infection. Due to the low production of gp120 proteins in CHO cells (2-20 mg/L), cleavage sites in V1V2 loops (A244) and V3 loop (MN) causing heterogeneous antigen products, it was an urgent need to generate CHO cells harboring A244 gp120 with high production yields and an additional, homogenous and uncleaved subtype B gp120 protein to replace MN used in RV144 for the future clinical trials. Here we describe the generation of Chinese Hamster Ovary (CHO) cell lines stably expressing vaccine HIV-1 Env antigens for these purposes: one expressing an HIV-1 subtype CRF01_AE A244 Env gp120 protein (A244.AE) and one expressing an HIV-1 subtype B 6240 Env gp120 protein (6240.B) suitable for possible future manufacturing of Phase I clinical trial materials with cell culture expression levels of over 100 mg/L. The antigenic profiles of the molecules were elucidated by comprehensive approaches including analysis with a panel of well-characterized monoclonal antibodies recognizing critical epitopes using Biacore and ELISA, and glycosylation analysis by mass spectrometry, which confirmed previously identified glycosylation sites and revealed unknown sites of O-linked and N-linked glycosylations at non-consensus motifs. Overall, the vaccines given with MF59 adjuvant induced higher and more rapid antibody (Ab) responses as well as higher Ab avidity than groups given with aluminum hydroxide. Also, bivalent proteins (A244.AE and 6240.B) formulated with MF59 elicited distinct V2-specific Abs to the epitope previously shown to correlate with decreased risk of HIV-1 infection in the RV144 trial. All together, these results provide critical information allowing the consideration of these candidate gp120 proteins for future clinical evaluations in combination with a potent adjuvant.

Objective: Incidence of lung cancer (LC) is increasing day by day with exposure to smoke, radiation, and chemicals; LC is one of the leading causes of death. The major difficulty in treatment was delayed diagnosis. This study aims to propose a time-domain heart rate variability (HRV) feature-based automated system in LC prediction and its staging., Materials and Methods: HRV analysis was done using recorded electrocardiographic signal from 104 LC participants and 30 control volunteers. Artificial neural network (ANN) and support vector machine (SVM) were implemented on HRV time-domain features for early prognosis of the disorder. Statistical significance of HRV parameters was tested, and graphical user interface (GUI) was also implemented., Results: It was revealed that progression of cancer causes low HRV. An accuracy of 89.64% and 100% was obtained with ANN and SVM, respectively, in automated cancer prediction. Statistical analysis suggested the significance of data at P < 0.05 between different performance statuses among patients., Conclusion: The severity of LC alters the sympathovagal balance through autonomic dysfunction. HRV analysis with an expert system was found useful for the early diagnosis of the disease, and thus, a noninvasive technique is of prognostic importance in classifying LC stages. The GUI designed for clinicians can help them to diagnose the Eastern Cooperative Oncology Group performance status scale of future patients., Competing Interests: There are no conflicts of interest

Human Cytomegalovirus (HCMV) is a major cause of morbidity and mortality in transplant patients and in fetuses following congenital infection. The glycoprotein complexes gH/gL/gO and gH/gL/UL128/UL130/UL131A (Pentamer) are required for HCMV entry in fibroblasts and endothelial/epithelial cells, respectively, and are targeted by potently neutralizing antibodies in the infected host. Using purified soluble forms of gH/gL/gO and Pentamer as well as a panel of naturally elicited human monoclonal antibodies, we determined the location of key neutralizing epitopes on the gH/gL/gO and Pentamer surfaces. Mass Spectrometry (MS) coupled to Chemical Crosslinking or to Hydrogen Deuterium Exchange was used to define residues that are either in proximity or part of neutralizing epitopes on the glycoprotein complexes. We also determined the molecular architecture of the gH/gL/gO- and Pentamer-antibody complexes by Electron Microscopy (EM) and 3D reconstructions. The EM analysis revealed that the Pentamer specific neutralizing antibodies bind to two opposite surfaces of the complex, suggesting that they may neutralize infection by different mechanisms. Together, our data identify the location of neutralizing antibodies binding sites on the gH/gL/gO and Pentamer complexes and provide a framework for the development of antibodies and vaccines against HCMV.

Aim: Withdrawal from dialysis is a common mode of death in patients undergoing dialysis. Anecdotally most patients have a physician-directed dialysis withdrawal (DW) following an acute medical precipitant, rather than a patient-narrated planned withdrawal as part of a collaborative end-of-life care plan. We report a 12-year retrospective experience of patients undergoing dialysis who died following DW, and suggest clinical parameters which can be used to identify patients who are able to direct their end-of-life care process., Methods: Retrospective 12-year review of inhouse electronic and paper records., Results: 867 patients undergoing dialysis died during the study period. 93 patients died from DW. 9 (10%) patients electively withdrew in the absence of an acute medical precipitant and 84(90%) withdrew from dialysis for medical reasons. Patients who chose to withdraw were 10 years younger at dialysis initiation and withdrawal, had greater reported sessional difficulties/intolerances (p<0.05), greater general deterioration in terms of comorbidity and physical dependency during the course of dialysis (p<0.05), were more likely to rehabilitate following an acute medical precipitant, and were more likely to reside in their own home on DW (p<0.05). All had decision-making capacity compared with 35(42%) patients who had dialysis withdrawn for medical reasons (p<0.05)., Conclusions: Comorbidity, physical dependence, dialysis tolerance, cognitive decline, rehabilitation post an acute medical precipitant and, place of residence are parameters which differentiate between patients who choose to withdraw from dialysis and those who have dialysis withdrawn for medical reasons. These parameters can be used to identify terminal patients on dialysis who are able to be directive in their end-of-life advanced care planning., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Respiratory syncytial virus (RSV) is the leading infectious cause of severe respiratory disease in infants and a major cause of respiratory illness in the elderly. There remains an unmet vaccine need despite decades of research. Insufficient potency, homogeneity, and stability of previous RSV fusion protein (F) subunit vaccine candidates have hampered vaccine development. RSV F and related parainfluenza virus (PIV) F proteins are cleaved by furin during intracellular maturation, producing disulfide-linked F1 and F2 fragments. During cell entry, the cleaved Fs rearrange from prefusion trimers to postfusion trimers. Using RSV F constructs with mutated furin cleavage sites, we isolated an uncleaved RSV F ectodomain that is predominantly monomeric and requires specific cleavage between F1 and F2 for self-association and rearrangement into stable postfusion trimers. The uncleaved RSV F monomer is folded and homogenous and displays at least two key RSV-neutralizing epitopes shared between the prefusion and postfusion conformations. Unlike the cleaved trimer, the uncleaved monomer binds the prefusion-specific monoclonal antibody D25 and human neutralizing immunoglobulins that do not bind to postfusion F. These observations suggest that the uncleaved RSV F monomer has a prefusion-like conformation and is a potential prefusion subunit vaccine candidate. Importance: RSV is the leading infectious cause of severe respiratory disease in infants and a major cause of respiratory illness in the elderly. Development of an RSV vaccine was stymied when a clinical trial using a formalin-inactivated RSV virus made disease, following RSV infection, more severe. Recent studies have defined the structures that the RSV F envelope glycoprotein adopts before and after virus entry (prefusion and postfusion conformations, respectively). Key neutralization epitopes of prefusion and postfusion RSV F have been identified, and a number of current vaccine development efforts are focused on generating easily produced subunit antigens that retain these epitopes. Here we show that a simple modification in the F ectodomain results in a homogeneous protein that retains critical prefusion neutralizing epitopes. These results improve our understanding of RSV F protein folding and structure and can guide further vaccine design efforts., (Copyright © 2014, American Society for Microbiology. All Rights Reserved.)

The present work is concerned to model the molecular signalling pathway for vasodilation and to predict the resting young human forearm blood flow under heat stress. The mechanistic electronic modelling technique has been designed and implemented using MULTISIM 8.0 and an assumption of 1V/ degrees C for prediction of forearm blood flow and the digital logic has been used to design the molecular signalling pathway for vasodilation. The minimum forearm blood flow has been observed at 35 degrees C (0 ml 100 ml(-1)min(-1)) and the maximum at 42 degrees C (18.7 ml 100 ml(-1)min(-1)) environmental temperature with respect to the base value of 2 ml 100 ml(-1)min(-1). This model may also enable to identify many therapeutic targets that can be used in the treatment of inflammations and disorders due to heat-related illnesses., (2010 Elsevier Ltd. All rights reserved.)

Objective: To examine the performance of Artificial Neural Network (ANN) in evaluation of the effects of pretreatment of para-Chlorophenylalanine (p-CPA), a serotonin blocker, in experimental brain injury., Methods: Continuous 4 h digital electroencephalogram (EEG) recordings from male Charles Foster rats and its power spectrum analysis by using fast Fourier transform (FFT) were performed in two experimental (i) drug untreated injury group; (ii) p-CPA pretreated injury group as well as a control group. The EEG power spectrum data were tested by ANN containing 60 nodes in input layer, weighted from the digital values of power spectrum from 0 to 30 Hz, 18 nodes in hidden layer and an output node. The effects of injury and of the drug pretreatment were confirmed with the help of calculation of edematous swelling in the brain., Results: The changes in EEG spectral patterns were compared with the ANN and the accuracy was determined in terms of percent (%). Overall performance of the network was found the best in control group (97.9%) in comparison to p-CPA untreated injury group (96.3%) and p-CPA pretreated injury group (71.9%). The decrease in accuracy in p-CPA pretreated injury group of subjects have occurred due to increase in misclassified patterns due to faster recovery in brain cortical potentials., Conclusion: EEG spectrum analysis with ANN was found successful in identifying the changes due to brain swelling as well as the effect of pretreatment of p-CPA in focal brain injury condition. Thus, the training and testing of ANN with EEG power spectra can be used as an effective diagnostic tool for early prediction and monitoring of brain injury as well as the effects of drugs in this condition.

Heat stress is known to induce high mortality rate due to multi-system illness, which demands urgent attention to reduce the fatality rate in such patients. Further, for the diagnosis and supportive therapy, one needs to define the severity of heat stress that can be distinguished as mild, intermediate and severe. The objective of this work is to develop an automated unsupervised artificial system to analyze the clinical outcomes of different levels of heat related illnesses. The Kohonen neural network program written in C++, which has seven normalized values of different clinical symptoms between 0-1 fed to the input layer of the network with 50 Kohonen output neurons, has been presented. The optimized initializing parameters such as neighborhood size and learning rate was set to 50 and 0.7, respectively, to simulate the network for 10 million iterations. The network was found smartly distinguishing all 51 patterns to three different states of heat illnesses. With the advent of these findings, it can be concluded that the Kohonen neural network can be used for automated classification of the severity of heat stress and other related psycho-patho-physiological disorders. However, to replace the expert clinicians with such type of smart diagnostic tool, extensive work is required to optimize the system with variety of known and hidden clinical and pathological parameters.

Many mathematical models of thermoregulation in humans have been developed, so far. These models appeared to be very useful tools for studying temperature regulation in humans under adverse environmental conditions. However, no one discussed the heat transfer characteristics of denervated subjects. Thus, the present study is concerned with aspects of the passive system for denervated subjects: (1) modeling the human body extremities (2) modeling heat transport mechanism within the body and at its periphery. The present model was simulated using the software (Wintherm 8.0, Thermoanalytics, USA) for different body segments to predict the heat flow between body core and skin surface with changes in environmental temperature with fixed relative humidity and wind velocity. The simulated model for comparative study of internal temperature distribution of hand, arm, leg and feet segments yielded remarkably good results and observed to be in trends with previously cited work under ambient environmental condition and at controlled room temperature. Models could be used to measure the temperature distribution in human limbs during local hyperthermia and to investigate the interaction between limbs and the thermal environment.

The effects of chronic exposure (2 h daily for 21 days) of 1 kHz square wave-modulated 2450 MHz microwave radiation (non-thermal) on sleep-EEG, open field behavior, and thyroid hormones (T(3), T(4), and TSH) have been analyzed in an animal model. Results revealed significant changes in these pathophysiological parameters (p < 0.05 or better), except body temperature, grooming behavior, and TSH levels. The sleep-EEG power spectrum data for slow wave sleep (SWS), rapid eye movement (REM) sleep, and awake (AWA) states in two experimental groups of rats (microwave exposed and the control) were tested by an artificial neural network (ANN), containing 60 nodes in input layer, weighted from power spectrum data from 0 to 30 Hz, 18 nodes in hidden layer and an output node. The target output values for this network were determined with another five-layered neural network (with the structure of 6-14-1-14-6). The input and output of this network was assigned with the six confirmed pathophysiological changes. The most important feature for chronic exposure of 2450 MHz microwave exposure and for control subjects was extracted from the third layer single neuron and used as the target value for the three-layered ANN. The network was found effective in recognizing the EEG power spectra with an average of 71.93% for microwave exposure and 93.13% for control subjects, respectively. However, the lower percentage of pattern identification agreement in the microwave-exposed group in comparison to the control group suggest only mild effects of microwave exposure with this experimental setup.

The thermoregulatory control of human skin blood flow is vital to maintain the body heat storage during challenges of thermal homeostasis under heat stress. Whenever thermal homeostasis disturbed, the heat load exceeds heat dissipation capacity, which alters the cutaneous vascular responses along with other body physiological variables. Whole body skin blood flow has been calculated from the forearm blood flow. Present model has been designed using electronics circuit simulator (Multisim 8.0, National Instruments, USA), is to execute a series of predictive equations for early prediction of physiological parameters of young nude subjects during resting condition at various level of dry heat stress under almost still air to avoid causalities associated with hot environmental. The users can execute the model by changing the environmental temperature in degrees C and exposure time in minutes. The model would be able to predict and detect the changes in human vascular responses along with other physiological parameters and from this predicted values heat related-illness symptoms can be inferred.

Exertional heat illness is primarily a multi-system disorder results from the combined effect of exertional and thermoregulation stress. The severity of exertional heat illness can be classified as mild, intermediate and severe from non-specific symptoms like thirst, myalgia, poor concentration, hysteria, vomiting, weakness, cramps, impaired judgement, headache, diarrhea, fatigue, hyperventilation, anxiety, and nausea to more severe symptoms like exertional dehydration, heat cramps, heat exhaustion, heat injury, heatstroke, rhabdomyolysis, and acute renal failure. At its early stage, it is quite difficult to find out the severity of disease with manual screening because of overlapping of symptoms. Therefore, one need to classify automatically the disease based on symptoms. The 7:10:1 backpropagation artificial neural network model has been used to predict the clinical outcome from the symptoms that are routinely available to clinicians. The model has found to be effective in differentiating the different stages of exertional heat-illness with an overall performance of 100%.

The phonocardiograph (PCG) can provide a noninvasive diagnostic ability to the clinicians and technicians to compare the heart acoustic signal obtained from normal and that of pathological heart (cardiac patient). This instrument was connected to the computer through the analog to digital (A/D) converter. The digital data stored for the normal and diseased (mitral valve regurgitation) heart in the computer were decomposed through the Coifman 4th order wavelet kernel. The decomposed phonocardiographic (PCG) data were tested by backpropagation artificial neural network (ANN). The network was containing 64 nodes in the input layer, weighted from the decomposed components of the PCG in the input layer, 16 nodes in the hidden layer and an output node. The ANN was found effective in differentiating the wavelet components of the PCG from mitral valve regurgitation confirmed person (93%) to normal subjects (98%) with an overall performance of 95.5%. This system can also be used to detect the defects in cardiac valves especially, and other several cardiac disorders in general.

This paper presents an effective application of backpropagation artificial neural network (ANN) in differentiating electroencephalogram (EEG) power spectra of syncopic and normal subjects. Digitized 8-channel EEG data were recorded with standard electrodes placement and amplifier settings from five confirmed syncopic and five normal subjects. The preprocessed EEG signals were fragmented in two-second artifact free epochs for calculation and analysis of changes due to syncope. The results revealed significant increase in percentage delta and alpha (p < 0.5 or better) with significant reduction in percentage theta activity (p < 0.05). The backpropagation ANN used for classification contains 60 nodes in input layer, weighted from power spectrum data from 0 to 30 Hz, 18 nodes in hidden layer and an output node. The ANN was found effective in differentiating the EEG power spectra from syncopic EEG power spectra and the normal EEG power spectra with an accuracy of 88.87% (85.75% for syncopic and 92% for normal).

Background: Serotonin is believed as an important factor in brain function. The role of serotonin in cerebral psycho-patho-physiology has already been well established. However, the function of serotonin antagonist in anesthetized subjects under hyperthermia has not been studied properly., Methods: Experiments were performed in three groups of urethane-anesthetized rats, such as: (i) control group, (ii) whole body hyperthermia group and (iii) p-CPA (para-Chlorophenylalanine) pretreated hyperthermia group. Hyperthermia was produced by subjecting the rats to high ambient temperature of 38 +/- 1 degrees C (relative humidity 45-50%). Each group was divided for EEG (electroencephalogram) study and for determination of edematous swelling in the brain., Results: Urethane anesthetized rats under hyperthermia show highly significant reduction in their survival time. The body temperature recorded during the hyperthermia was observed with significant and linear rise with marked increase in brain water content, which was analyzed just after the death of the subjects. The results of the electroencephalographic study in urethane-anesthetized rats recorded before death indicate that brain function varies in systematic manner during hyperthermia as sequential changes in EEG patterns were observed. However, a serotonin antagonist, p-CPA pretreatment increases the survival time with significant reduction in edematous swelling in brain but it does not affect the relationship between the core body temperature and the brain cortical potentials as observed in urethane anesthetized subjects exposed to whole body hyperthermia. The core body temperature in p-CPA pretreated rats show non-linear relationship with respect to the exposure time as it was observed in drug untreated subjects., Conclusion: The findings of the present study indicate that although pretreatment of p-CPA in rats has a marked correlation between the extravasations of the blood-brain barrier under hyperthermia but shows minimum effect on the EEG in a model of hyperthermia under irreversible anesthesia.