Combating antimicrobial resistance: the silent war

Once hailed as miraculous solutions, antibiotics no longer hold that status. The excessive use of antibiotics across human healthcare, agriculture, and animal husbandry has given rise to a broad array of multidrug-resistant (MDR) pathogens, posing formidable treatment challenges. Antimicrobial resistance (AMR) has evolved into a pressing global health crisis, linked to elevated mortality rates in the modern medical era. Additionally, the absence of effective antibiotics introduces substantial risks to medical and surgical procedures. The dwindling interest of pharmaceutical industries in developing new antibiotics against MDR pathogens has aggravated the scarcity issue, resulting in an exceedingly limited pipeline of new antibiotics. Given these circumstances, the imperative to devise novel strategies to combat perilous MDR pathogens has become paramount. Contemporary research has unveiled several promising avenues for addressing this challenge. The article provides a comprehensive overview of these innovative therapeutic approaches, highlighting their mechanisms of action, benefits, and drawbacks

Therapeutic evolution in HR+/HER2- breast cancer: from targeted therapy to endocrine therapy

Breast cancer, a complex and varied disease, has four distinct subtypes based on estrogen receptor and human epidermal growth factor receptor 2 (HER2) levels, among which a significant subtype known as HR+/HER2-breast cancer that has spurred numerous research. The prevalence of breast cancer and breast cancer-related death are the most serious threats to women’s health worldwide. Current progress in treatment strategies for HR+/HER2-breast cancer encompasses targeted therapy, endocrine therapy, genomic immunotherapy, and supplementing traditional methods like surgical resection and radiotherapy. This review article summarizes the current epidemiology of HR+/HER2-breast cancer, introduces the classification of HR+/HER2-breast cancer and the commonly used treatment methods. The mechanisms of action of various drugs, including targeted therapy drugs and endocrine hormone therapy drugs, and their potential synergistic effects are deeply discussed. In addition, clinical trials of these drugs that have been completed or are still in progress are included

Volumetric Diffuse Optical Tomography for Small Animals Using a CCD-Camera-Based Imaging System

We report the feasibility of three-dimensional (3D) volumetric diffuse optical tomography for small animal imaging by using a CCD-camera-based imaging system with a newly developed depth compensation algorithm (DCA). Our computer simulations and laboratory phantom studies have demonstrated that the combination of a CCD camera and DCA can significantly improve the accuracy in depth localization and lead to reconstruction of 3D volumetric images. This approach may present great interests for noninvasive 3D localization of an anomaly hidden in tissue, such as a tumor or a stroke lesion, for preclinical small animal models

Comprehensive investigation of three-dimensional diffuse optical tomography with depth compensation algorithm

A depth compensation algorithm (DCA) can effectively improve the depth localization of diffuse optical tomography (DOT) by compensating the exponentially decreased sensitivity in the deep tissue. In this study, DCA is investigated based on computer simulations, tissue phantom experiments, and human brain imaging. The simulations show that DCA can largely improve the spatial resolution of DOT in addition to the depth localization, and DCA is also effective for multispectral DOT with a wide range of optical properties in the background tissue. The laboratory phantom experiment demonstrates that DCA can effectively differentiate two embedded objects at different depths in the medium. DCA is further validated by human brain imaging using a finger-tapping task. To our knowledge, this is the first demonstration to show that DCA is capable of accurately localizing cortical activations in the human brain in three dimensions

Resting-state functional connectivity assessed with two diffuse optical tomographic systems

Functional near-infrared spectroscopy (fNIRS) is recently utilized as a new approach to assess resting-state functional connectivity (RSFC) in the human brain. For any new technique or new methodology, it is necessary to be able to replicate similar experiments using different instruments in order to establish its liability and reproducibility. We apply two different diffuse optical tomographic (DOT) systems (i.e., DYNOT and CW5), with various probe arrangements to evaluate RSFC in the sensorimotor cortex by utilizing a previously published experimental protocol and seed-based correlation analysis. Our results exhibit similar spatial patterns and strengths in RSFC between the bilateral motor cortexes. The consistent observations are obtained from both DYNOT and CW5 systems, and are also in good agreement with the previous fNIRS study. Overall, we demonstrate that the fNIRS-based RSFC is reproducible by various DOT imaging systems among different research groups, enhancing the confidence of neuroscience researchers and clinicians to utilize fNIRS for future applications

Early detection of all-zero 4 x 4 blocks in High Efficiency Video Coding

Similar to previous video coding standards, transform and quantization are employed in the most recent video coding standard High Efficiency Video Coding (HEVC), and there exist a large number of transform coefficients being quantized to zeros. In order to reduce the computations in transform and quantization, a novel prediction algorithm is designed to early detect all-zero 4 x 4 blocks prior to transform and quantization. A theoretical analysis is performed on the 4 x 4 Discrete Cosine Transform (DCT) and the related quantization functions in HEVC; consequently, two sufficient conditions to early detect all-zero 4 x 4 blocks are derived and the proposed prediction algorithm is developed while balancing the detection efficiency and computational overheads. Experimental results demonstrate that the proposed algorithm is able to efficiently predict all-zero 4 x 4 blocks and reduce redundant DCT and quantization computations while maintaining the same coding performance in terms of video quality and bit rates. (C) 2014 Elsevier Inc. All rights reserved

Informative priors on fetal fraction increase power of the noninvasive prenatal screen

Noninvasive prenatal screening (NIPS) sequences a mixture of the maternal and fetal cell-free DNA. Fetal trisomy can be detected by examining chromosomal dosages estimated from sequencing reads. The traditional method uses the Z-test, which compares a subject against a set of euploid controls, where the information of fetal fraction is not fully utilized. Here we present a Bayesian method that leverages informative priors on the fetal fraction. Our Bayesian method combines the Z-test likelihood and informative priors of the fetal fraction, which are learned from the sex chromosomes, to compute Bayes factors. Bayesian framework can account for nongenetic risk factors through the prior odds, and our method can report individual positive/negative predictive values. Our Bayesian method has more power than the Z-test method. We analyzed 3,405 NIPS samples and spotted at least 9 (of 51) possible Z-test false positives. Bayesian NIPS is more powerful than the Z-test method, is able to account for nongenetic risk factors through prior odds, and can report individual positive/negative predictive values