Association of HLA gene polymorphisms with Helicobacter pylori related gastric cancer-a systematic review.

The appropriate host cell immune responses for the progression of several diseases, including gastric or stomach cancer (GC), are significantly influenced by HLA polymorphisms. Our objective was to systematically review the evidence linking HLA polymorphisms with the risk of Helicobacter. pylori related GC. We conducted a comprehensive literature search to identify studies published between 2000 and April 2023 on the association of HLA polymorphisms with H. pylori related GC using databases such as Medline through PubMed, Embase, Web of Science (core collection), The Cochrane Library, and Scopus. Two authors independently screened articles, extracted data, and assessed the risk of bias using the Risk of Bias Assessment tool for Non-randomized Studies. From 7872 retrieved studies, 19 met inclusion criteria, encompassing 1656 cases and 16,787 controls across four World Health Organization regions, with Japan contributing the most studies. We explored HLA-A/B/C, HLA-DRB1/DQA1/DQB1, HLA-G, and MICA alleles. Of 29 significant HLA polymorphisms identified, 18 showed a positive association with GC, whereas 11 were negatively associated. HLA-DQB1*06 allele was most frequently associated to susceptibility, as reported in four studies, followed by HLA-DRB1*04 and HLA-DQA1*01, each reported in two studies. Conversely, HLA-G*01, HLA-DQA1*01, HLA-DQA1*05, and HLA-DQB1*03 were identified as protective in two studies each. Additionally, five genotypes and six haplotypes were reported as positive, whereas three genotypes and two haplotypes were negative factors for the disease incidence or mortality. Despite heterogeneity in the study population and types of HLA polymorphisms examined, our analysis indicates certain polymorphisms are associated with H. pylori related GC progression and mortality in specific populations.

Optimization of Microchannels and Application of Basic Activation Functions of Deep Neural Network for Accuracy Analysis of Microfluidic Parameter Data.

The fabrication of microflow channels with high accuracy in terms of the optimization of the proposed designs, minimization of surface roughness, and flow control of microfluidic parameters is challenging when evaluating the performance of microfluidic systems. The use of conventional input devices, such as peristaltic pumps and digital pressure pumps, to evaluate the flow control of such parameters cannot confirm a wide range of data analysis with higher accuracy because of their operational drawbacks. In this study, we optimized the circular and rectangular-shaped microflow channels of a 100 µm microfluidic chip using a three-dimensional simulation tool, and analyzed concentration profiles of different regions of the microflow channels. Then, we applied a deep learning (DL) algorithm for the dense layers of the rectified linear unit (ReLU), Leaky ReLU, and Swish activation functions to train and test 1600 experimental and interpolation of data samples which obtained from the microfluidic chip. Moreover, using the same DL algorithm, we configured three models for each of these three functions by changing the internal middle layers of these models. As a result, we obtained a total of 9 average accuracy values of ReLU, Leaky ReLU, and Swish functions for a defined threshold value of 6×10-5 using the trial-and-error method. We applied single-to-five-fold cross-validation technique of deep neural network to avoid overfitting and reduce noises from data-set to evaluate better average accuracy of data of microfluidic parameters.

Peptidoglycan Recycling Promotes Outer Membrane Integrity and Carbapenem Tolerance in Acinetobacter baumannii.

ß-Lactam antibiotics exploit the essentiality of the bacterial cell envelope by perturbing the peptidoglycan layer, typically resulting in rapid lysis and death. Many Gram-negative bacteria do not lyse but instead exhibit "tolerance," the ability to sustain viability in the presence of bactericidal antibiotics for extended periods. Antibiotic tolerance has been implicated in treatment failure and is a stepping-stone in the acquisition of true resistance, and the molecular factors that promote intrinsic tolerance are not well understood. Acinetobacter baumannii is a critical-threat nosocomial pathogen notorious for its ability to rapidly develop multidrug resistance. Carbapenem ß-lactam antibiotics (i.e., meropenem) are first-line prescriptions to treat A. baumannii infections, but treatment failure is increasingly prevalent. Meropenem tolerance in Gram-negative pathogens is characterized by morphologically distinct populations of spheroplasts, but the impact of spheroplast formation is not fully understood. Here, we show that susceptible A. baumannii clinical isolates demonstrate tolerance to high-level meropenem treatment, form spheroplasts upon exposure to the antibiotic, and revert to normal growth after antibiotic removal. Using transcriptomics and genetic screens, we show that several genes associated with outer membrane integrity maintenance and efflux promote tolerance, likely by limiting entry into the periplasm. Genes associated with peptidoglycan homeostasis in the periplasm and cytoplasm also answered our screen, and their disruption compromised cell envelope barrier function. Finally, we defined the enzymatic activity of the tolerance determinants penicillin-binding protein 7 (PBP7) and ElsL (a cytoplasmic ld-carboxypeptidase). These data show that outer membrane integrity and peptidoglycan recycling are tightly linked in their contribution to A. baumannii meropenem tolerance. IMPORTANCE Carbapenem treatment failure associated with "superbug" infections has rapidly increased in prevalence, highlighting the urgent need to develop new therapeutic strategies. Antibiotic tolerance can directly lead to treatment failure but has also been shown to promote the acquisition of true resistance within a population. While some studies have addressed mechanisms that promote tolerance, factors that underlie Gram-negative bacterial survival during carbapenem treatment are not well understood. Here, we characterized the role of peptidoglycan recycling in outer membrane integrity maintenance and meropenem tolerance in A. baumannii. These studies suggest that the pathogen limits antibiotic concentrations in the periplasm and highlight physiological processes that could be targeted to improve antimicrobial treatment.

Sensitivity Enhancement of Modified D-Shaped Microchannel PCF-Based Surface Plasmon Resonance Sensor.

In this work, a highly sensitive dual-core configured microchannel-based plasmonic refractive index (RI) sensor was investigated, which can be used for low RI detection. Both the sensing layer and the plasmonic material layer were built outside of the fiber design to detect the surrounding medium's RI changes. Additionally, the effects of different plasmonic materials gold (Au), silver (Ag), and copper (Cu) toward sensitivity were investigated for the same structure. An adhesive agent was used in this work, titanium dioxide (TiO2), and was coated on top of the plasmonic material to prevent the oxidation of Ag and Cu. The coupling strength between the fundamental mode and the surface plasmon polariton (SPP) mode was observed to be very strong due to the TiO2 adhesive agent. With a resolution of 7.41 × 10-7 RIU, maximum wavelength sensitivity (WS) of 135,000 nm/RIU and amplitude sensitivity (AS) of 3239 RIU-1 were achieved using the proposed sensor while using Au as a plasmonic material for an analyte RI range of 1.29-1.39. A detailed study of relevant literature revealed that the achieved wavelength sensitivity for plasmonic material gold (Au) is the highest among reported photonic crystal fiber (PCF)-surface plasmon resonance (SPR) sensors to date.

A Bimetallic-Coated, Low Propagation Loss, Photonic Crystal Fiber Based Plasmonic Refractive Index Sensor.

In this paper, a low-loss, spiral lattice photonic crystal fiber (PCF)-based plasmonic biosensor is proposed for its application in detecting various biomolecules (i.e., sugar, protein, DNA, and mRNA) and biochemicals (i.e., serum and urine). Plasmonic material gold (Au) is employed externally to efficiently generate surface plasmon resonance (SPR) in the outer surface of the PCF. A thin layer of titanium oxide (TiO2) is also introduced, which assists in adhering the Au layer to the silica fiber. The sensing performance is investigated using a mode solver based on the finite element method (FEM). Simulation results show a maximum wavelength sensitivity of 23,000 nm/RIU for a bio-samples refractive index (RI) detection range of 1.32-1.40. This sensor also exhibits a very low confinement loss of 0.22 and 2.87 dB/cm for the analyte at 1.32 and 1.40 RI, respectively. Because of the ultra-low propagation loss, the proposed sensor can be fabricated within several centimeters, which reduces the complexity related to splicing, and so on.

Microchannel-based plasmonic refractive index sensor for low refractive index detection.

A microchannel incorporated photonic crystal fiber (PCF)-based surface plasmon resonance (SPR) sensor for detection of low refractive index (RI) at near-infrared wavelength is presented in this paper. To attain a simple and practically feasible mechanism, plasmonic material gold (Au) and sensing medium are placed outside the fiber. A thin layer of TiO2 is employed as an adhesive layer to strongly attach the Au with the silica glass. In the sensing range of 1.22 to 1.37, maximum sensitivities of 51,000 nm/RIU (RI unit) and 1872 RIU-1 are obtained with resolutions of 1.96×10-6 and 9.09×10-6 RIUs using wavelength and amplitude interrogation methods, respectively. To the best of the authors' knowledge, the obtained maximum wavelength sensitivity and resolution are the highest among reported PCF-based SPR sensors to date. The sensor also exhibits a maximum figure of merit of 566. Therefore, the proposed sensor would be an excellent candidate for a wide range of RI detection with higher accuracy for applications such as pharmaceutical inspection and leakage monitoring, bio-sensing, and other low RI analytes.