Bevacizumab-induced immune thrombocytopenia in an ovarian cancer patient with mixed connective tissue disease: case report and literature review

Drug-induced immune thrombocytopenia is an adverse reaction marked by accelerated destruction of blood platelets. In cancer therapy, thrombocytopenia has many other causes including bone marrow suppression induced by chemotherapeutic agents, infection, and progression of cancer; drug-induced thrombocytopenia can easily be misdiagnosed or overlooked. Here, we present a case of an ovarian cancer patient with a history of mixed connective tissue disease who underwent surgery followed by treatment with paclitaxel, cisplatin, and bevacizumab. The patient developed acute isolated thrombocytopenia after the sixth cycle. Serum antiplatelet antibody testing revealed antibodies against glycoprotein IIb. After we analyzed the whole therapeutic process of this patient, drug-induced immune thrombocytopenia was assumed, and bevacizumab was conjectured as the most probable drug. Thrombocytopenia was ultimately successfully managed using recombinant human thrombopoietin, prednisone, and recombinant human interleukin-11. We provide a summary of existing literature on immune thrombocytopenia induced by bevacizumab and discuss related mechanisms and triggers for drug-induced immune thrombocytopenia. The present case underscores the potential of bevacizumab to induce immune-mediated thrombocytopenia, emphasizing the need for heightened vigilance towards autoimmune diseases or an autoimmune-activated state as plausible triggers for rare drug-induced immune thrombocytopenia in cancer therapy

Metagenomic insight into the global dissemination of the antibiotic resistome

The global crisis in antimicrobial resistance continues to grow. Estimating the risks of antibiotic resistance transmission across habitats is hindered by the lack of data on mobility and habitat-specificity. Metagenomic samples of 6092 are analyzed to delineate the unique core resistomes from human feces and seven other habitats. This is found that most resistance genes (≈85%) are transmitted between external habitats and human feces. This suggests that human feces are broadly representative of the global resistome and are potentially a hub for accumulating and disseminating resistance genes. The analysis found that resistance genes with ancient horizontal gene transfer (HGT) events have a higher efficiency of transfer across habitats, suggesting that HGT may be the main driver for forming unique but partly shared resistomes in all habitats. Importantly, the human fecal resistome is historically different and influenced by HGT and age. The most important routes of cross-transmission of resistance are from the atmosphere, buildings, and animals to humans. These habitats should receive more attention for future prevention of antimicrobial resistance. The study will disentangle transmission routes of resistance genes between humans and other habitats in a One Health framework and can identify strategies for controlling the ongoing dissemination and antibiotic resistance

Eff ect of a comprehensive programme to provide universal access to care for sputum-smear-positive multidrugresistant tuberculosis in China: a before-and-after study

Background China has a quarter of all patients with multidrug-resistant tuberculosis (MDRTB) worldwide, but less than 5% are in quality treatment programmes. In a before-and-after study we aimed to assess the eff ect of a comprehensive programme to provide universal access to diagnosis, treatment, and follow-up for MDRTB in four Chinese cities (population 18 million). Methods We designated city-level hospitals in each city to diagnose and treat MDRTB. All patients with smear-positive pulmonary tuberculosis diagnosed in Center for Disease Control (CDC) clinics and hospitals were tested for MDRTB with molecular and conventional drug susceptibility tests. Patients were treated with a 24 month treatment package for MDRTB based on WHO guidelines. Outpatients were referred to the CDC for directly observed therapy. We capped total treatment package cost at US$4644. Insurance reimbursement and project subsidies limited patients’ expenses to 10 (2011) to those from a retrospective survey of all patients with MDRTB diagnosed in the same cities during a baseline period (2006–09). Findings 243 patients were diagnosed with MDRTB or rifampicin-resistant tuberculosis during the 12 month programme period compared with 92 patients (equivalent to 24 per year) during the baseline period. 172 (71 243 individuals were enrolled in the programme. Time from specimen collection for resistance testing to treatment initiation decreased by 90 started on appropriate drug regimen increased 2·7 times (from nine [35 172), and follow-up by the CDC after initial hospitalisation increased 24 times (from one [4 163 [99 increased ten times (from two [8 programme period had negative cultures or clinical–radiographic improvement. Patients’ expenses for hospital admission after MDRTB diagnosis decreased by 78$796 to $174), reducing the ratio of patients’ expenses to annual household income from 17·6% to 3·5% (p<0·0001 for all comparisons between baseline and programme periods). However, 36 (15%) patients did not start or had to discontinue treatment in the programme period because of fi nancial diffi culties. Interpretation This comprehensive programme substantially increased access to diagnosis, quality treatment, and aff ordable treatment for MDRTB. The programme could help China to achieve universal access to MDRTB care but greater fi nancial risk protection for patients is needed

Treatment Effect Models for Subgroup Analysis with Missing Data

The need for subgroup analysis in clinical trials in various contexts is increasing and data-driven approaches for subgroup identification based on statistical principles are desired. Among all subgroup identification methods, we focus on the treatment effect models that estimate the treatment contrast, since these models are intuitive and useful to interpretation. We evaluate and address the consequences of having missing data when using the Interaction Trees (IT), Qualitative Interaction Trees (QUINT) and Subgroup Identification based on Differential Effect Search (SIDES) methods. Simulation studies are used to demonstrate the accuracy of variable selection and bias in treatment effects when using complete, incomplete and imputed data across various scenarios when the sample size, proportion of missingness and imputation methods differ. We also applied these methods to a non-small cell lung cancer (NSCLC) dataset obtained from a retrospective study. Our results indicate that both IT and QUINT methods work equivalently well in most situations, while the SIDES results are, in general, less comparable due to the different mechanisms of the methods. The treatment effect models should be chosen based on the objective of the study, the sample size, the number of variables containing missing data, and the data structure. In terms of the methods for addressing missing data, an assumption of the data structure needs to be made during the method selection. MissForest is an excellent choice for a dataset with a tree-based structure, while MI methods would be a good fit for the other situations

Chloroplasts Protein Quality Control and Turnover: A Multitude of Mechanisms

As the organelle of photosynthesis and other important metabolic pathways, chloroplasts contain up to 70% of leaf proteins with uniquely complex processes in synthesis, import, assembly, and turnover. Maintaining functional protein homeostasis in chloroplasts is vitally important for the fitness and survival of plants. Research over the past several decades has revealed a multitude of mechanisms that play important roles in chloroplast protein quality control and turnover under normal and stress conditions. These mechanisms include: (i) endosymbiotically-derived proteases and associated proteins that play a vital role in maintaining protein homeostasis inside the chloroplasts, (ii) the ubiquitin-dependent turnover of unimported chloroplast precursor proteins to prevent their accumulation in the cytosol, (iii) chloroplast-associated degradation of the chloroplast outer-membrane translocon proteins for the regulation of chloroplast protein import, (iv) chloroplast unfolded protein response triggered by accumulated unfolded and misfolded proteins inside the chloroplasts, and (v) vesicle-mediated degradation of chloroplast components in the vacuole. Here, we provide a comprehensive review of these diverse mechanisms of chloroplast protein quality control and turnover and discuss important questions that remain to be addressed in order to better understand and improve important chloroplast functions

Passive None-line-of-sight imaging with arbitrary scene condition and detection pattern in small amount of prior data

Passive Non-Line-of-Sight (NLOS) imaging requires to reconstruct objects which cannot be seen in line without using external controllable light sources. It can be widely applied in areas like counter-terrorism, urban-Warfare, autonomous-driving and robot-vision. Existing methods for passive NLOS typically required extensive prior information and significant computational resources to establish light transport matrices or train neural networks. These constraints pose significant challenges for transitioning models to different NLOS scenarios. Thus, the pressing issue in passive NLOS imaging currently lies in whether it is possible to estimate the light transport matrices which corresponding to relay surfaces and scenes, as well as the specific distribution of targets, with a small amount of prior knowledge. In this work, we hypothesized a high-dimensional manifold and mathematically proved its existence. Within this high-dimensional manifold, the structural information of obscured targets is minimally disrupted. Therefore, we proposed a universal framework named High-Dimensional Projection Selection (HDPS) which can establish this high-dimensional manifold and output its projection onto corresponding surfaces on low-dimensional. HDPS can be applied to most mature network architectures and estimate the distribution of target and light spot obtained by camera with only minimal prior data. Certainly, with the help of the estimated information, it can establish a high-dimensional manifold consisting of target and input. As demonstrated in experiment, our framework, even when applied to the most basic network structures, can achieve higher accuracy results with significantly smaller amounts of prior data. Thereby, our approach enables passive NLOS scenarios to reconstruct target by limited prior data and computational resources

Delayed Colorectal Cancer Diagnosis during the COVID-19 Pandemic in Alberta: A Framework for Analyzing Barriers to Diagnosis and Generating Evidence to Support Health System Changes Aimed at Reducing Time to Diagnosis

The frequency of colorectal cancer (CRC) diagnosis has decreased due to the COVID-19 pandemic. Health system planning is needed to address the backlog of undiagnosed patients. We developed a framework for analyzing barriers to diagnosis and estimating patient volumes under different system relaunch scenarios. This retrospective study included CRC cases from the Alberta Cancer Registry for the pre-pandemic (1 January 2016–4 March 2020) and intra-pandemic (5 March 2020–1 July 2020) periods. The data on all the diagnostic milestones in the year prior to a CRC diagnosis were obtained from administrative health data. The CRC diagnostic pathways were identified, and diagnostic intervals were measured. CRC diagnoses made during hospitalization were used as a proxy for severe disease at presentation. A modified Poisson regression analysis was used to estimate the adjusted relative risk (adjRR) and a 95% confidence interval (CI) for the effect of the pandemic on the risk of hospital-based diagnoses. During the study period, 8254 Albertans were diagnosed with CRC. During the pandemic, diagnosis through asymptomatic screening decreased by 6·5%. The adjRR for hospital-based diagnoses intra-COVID-19 vs. pre-COVID-19 was 1.24 (95% CI: 1.03, 1.49). Colonoscopies were identified as the main bottleneck for CRC diagnoses. To clear the backlog before progression is expected, high-risk subgroups should be targeted to double the colonoscopy yield for CRC diagnosis, along with the need for a 140% increase in monthly colonoscopy volumes for a period of 3 months. Given the substantial health system changes required, it is unlikely that a surge in CRC cases will be diagnosed over the coming months. Administrators in Alberta are using these findings to reduce wait times for CRC diagnoses and monitor progression

Source forensics of inorganic and organic nitrogen using delta N-15 for tropospheric aerosols over Mt. Tai

Nitrogen-containing species are major components in atmospheric aerosols. However, little is known about the sources of N-containing aerosols over high mountainous regions, especially for organic nitrogen (ON). This study aims to reveal the emission sources of both inorganic and organic nitrogen in tropospheric aerosols atop Mt. Tai, China, and to improve our understanding of the N cycle imbalance in the North China Plain (NCP). Total suspended particle (TSP) samples were collected on a daytime/nighttime basis in spring 2017 and were investigated for the concentrations and stable N isotopic compositions of total nitrogen, NH4+, NO3- and ON. Our results show that the concentrations of N-containing compounds were higher in daytime than nighttime, mainly resulting from mountain-valley breezes and the changes of planetary boundary layer height. However, no significant day/nighttime changes were found for their corresponding delta N-15 values, indicating similar contributions from different N sources between day and night. The MixSIAR Bayesian stable isotope mixing model results suggest that the most important emission source of NH3 for aerosol NH4+ was agriculture, followed by fossil fuel-related sources, human waste and biomass burning. Aerosol NO3- was mainly formed from combustion and mobile emitted NOx. Interestingly, the isotopes of ON suggest that ON were very likely firstly of primary origin. Our study reveals the characteristics of reactive N emission sources and helps understand the regional transport of tropospheric N-containing aerosols in the NCP