Artificial Intelligence (AI) Reveals Ethnic Disparities in Cataract Detection and Treatment

Introduction: The aim of this work is to identify patients at risk of limited access to healthcare through artificial intelligence using a name-ethnicity classifier (NEC) analyzing the clinical stage of cataract at diagnosis and preoperative visual acuity. Methods: This retrospective, cross-sectional study includes patients seen in the cataract clinic of a tertiary care hospital between September 2017 and February 2020 with subsequent cataract surgery in at least one eye. We analyzed 4971 patients and 8542 eyes undergoing surgery. Results: The NEC identified 360 patients with names classified as ‘non-German’ compared to 4611 classified as ‘German’. Advanced cataract (7 vs. 5%; p = 0.025) was significantly associated with group ‘non-German’. Mean best-corrected visual acuity in group ‘non-German’ was 0.464 ± 0.406 (LogMAR), and in group ‘German’ was 0.420 ± 0.334 (p = 0.009). This difference remained significant after exclusion of patients with non-lenticular ocular comorbidities. Surgical time and intraoperative complications did not differ between the groups. Retrobulbar or general anesthesia was chosen significantly more frequently over topical anesthesia in group ‘non-German’ compared to group ‘German’ (24 vs. 18% respectively; p < 0.001). Conclusions: This study shows that artificial intelligence is able to uncover health disparities between people with German compared to non-German names using NECs. Patients with non-German names, possibly facing various social barriers to healthcare access such as language barriers, have more advanced cataracts and worse visual acuity upon presentation. Artificial intelligence may prove useful for healthcare providers to discover and counteract such inequalities and establish tailored preventive measures to decrease morbidity in vulnerable population subgroups

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity

Eight Up-Coming Biotech Tools to Combat Climate Crisis

Biotechnology has a high potential to substantially contribute to a low-carbon society. Several green processes are already well established, utilizing the unique capacity of living cells or their instruments. Beyond that, the authors believe that there are new biotechnological procedures in the pipeline which have the momentum to add to this ongoing change in our economy. Eight promising biotechnology tools were selected by the authors as potentially impactful game changers: (i) the Wood-Ljungdahl pathway, (ii) carbonic anhydrase, (iii) cutinase, (iv) methanogens, (v) electro-microbiology, (vi) hydrogenase, (vii) cellulosome and, (viii) nitrogenase. Some of them are fairly new and are explored predominantly in science labs. Others have been around for decades, however, with new scientific groundwork that may rigorously expand their roles. In the current paper, the authors summarize the latest state of research on these eight selected tools and the status of their practical implementation. We bring forward our arguments on why we consider these processes real game changers

A Simple and Straightforward Method for Activity Measurement of Carbonic Anhydrases

Carbonic anhydrase (CA) is an enzyme of high interest due to its high implications relative to the medical and environmental sectors. In the current paper, an enzyme assay for the determination of CA activity is proposed and it is characterized by its simplicity and high practicability. It permits the straightforward comparison of CAs performance in physiological conditions. The methodology and the theoretical background of the evaluation method are explained in detail. Moreover, the presumed advantages over alternative assays are discussed. The assay has proven to be particularly useful for the screening of CA activity with respect to their application in CO2, capturing processes for further utilization or storage

Artificial Intelligence (AI) Reveals Ethnic Disparities in Cataract Detection and Treatment.

INTRODUCTION: The aim of this work is to identify patients at risk of limited access to healthcare through artificial intelligence using a name-ethnicity classifier (NEC) analyzing the clinical stage of cataract at diagnosis and preoperative visual acuity. METHODS: This retrospective, cross-sectional study includes patients seen in the cataract clinic of a tertiary care hospital between September 2017 and February 2020 with subsequent cataract surgery in at least one eye. We analyzed 4971 patients and 8542 eyes undergoing surgery. RESULTS: The NEC identified 360 patients with names classified as 'non-German' compared to 4611 classified as 'German'. Advanced cataract (7 vs. 5%; p = 0.025) was significantly associated with group 'non-German'. Mean best-corrected visual acuity in group 'non-German' was 0.464 ± 0.406 (LogMAR), and in group 'German' was 0.420 ± 0.334 (p = 0.009). This difference remained significant after exclusion of patients with non-lenticular ocular comorbidities. Surgical time and intraoperative complications did not differ between the groups. Retrobulbar or general anesthesia was chosen significantly more frequently over topical anesthesia in group 'non-German' compared to group 'German' (24 vs. 18% respectively; p < 0.001). CONCLUSIONS: This study shows that artificial intelligence is able to uncover health disparities between people with German compared to non-German names using NECs. Patients with non-German names, possibly facing various social barriers to healthcare access such as language barriers, have more advanced cataracts and worse visual acuity upon presentation. Artificial intelligence may prove useful for healthcare providers to discover and counteract such inequalities and establish tailored preventive measures to decrease morbidity in vulnerable population subgroups

Immune Response to Third and Fourth COVID-19 Vaccination in Hemodialysis Patients and Kidney Transplant Recipients

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) is a serious hazard for hemodialysis (HD) patients and kidney transplant (KTX) recipients as they suffer from an impaired immune response to SARS-CoV-2 vaccination. In addition, a definition of SARS-CoV-2 IgG titer that indicates a sufficient immune response, especially against new omicron variants, is urgently needed. In the present study, the immune response to either a third or a fourth dose of a mRNA vaccine was investigated in 309 dialysis and 36 KTX patients. SARS-CoV-2 IgG titer thresholds indicating neutralizing activity against wild type (WT) and the omicron variant BA.1 were quantified. After four vaccine doses, a high-neutralizing activity against WT was evidenced in HD patients, whereas the neutralizing rate against BA.1 was significant lower. Concerning KTX recipients, humoral and cellular immune responses after a third vaccination were still highly impaired. This calls for modified omicron-targeting vaccines

Immune Responses to SARS-CoV-2 Infection and Vaccination in Dialysis Patients and Kidney Transplant Recipients

Dialysis patients and kidney transplant (KTX) recipients suffer from an impaired immune system and show a decreased response to the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) vaccination. We performed a retrospective analysis of 1505 serological SARS-CoV-2 measurements obtained from 887 dialysis patients and 86 KTX recipients. The results were separated by patient subgroups (dialysis/KTX) as well as SARS-CoV-2 status. The latter criterion included SARS-CoV-2-na&iuml;ve patients with or without COVID-19 vaccination and convalescent patients receiving a booster shot. Serologies of 27 vaccinated healthy individuals served as the reference group. Vaccine-induced cellular immune response was quantified by an interferon-&gamma; release assay in 32 KTX recipients. We determined seroconversion rates of 92.6%, 93.4%, and 71.4% in dialysis patients vaccinated with either BNT162b2, mRNA-1273, or AZD1222, respectively. Vaccination-induced anti-SARS-CoV-2 antibody titers were lower in dialysis patients compared to healthy individuals, and vaccination with mRNA-1273 induced higher titers than BNT162b2. The initial seroconversion rate was 39.5% in KTX recipients vaccinated with BNT162b2. A linear regression model identified medication with mycophenolate-mofetil/mycophenolic acid as an independent risk factor for missing seroconversion. Within a cohort of 32 KTX recipients, cellular and humoral immune reactivity to SARS-CoV-2 was detectable in three patients only. Conclusively, vaccine-induced seroconversion rates were similar in dialysis patients compared to healthy individuals but were strongly impaired in KTX recipients. Anti-SARS-CoV-2 IgG titers elicited by double active immunization were significantly lower in both cohorts compared to healthy individuals, and immune responses to vaccination vanished quickly

Targeting HSP90 dimerization via the C-terminus is effective in imatinib resistant CML and lacks heat shock response

Heat shock protein 90 (HSP90) stabilizes many client proteins including BCR-ABL1 oncoprotein. BCR-ABL1 is the hallmark of CML in which treatment-free remission (TFR) is limited with clinical and economic consequences. Thus, there is an urgent need for novel therapeutics, which synergize with current treatment approaches. Several inhibitors targeting the N-terminal domain (NTD) of HSP90 are under investigation; however, side effects such as induction of heat shock response (HSR) and toxicity have so far precluded their FDA approval. We have developed a novel inhibitor (referred to as aminoxyrone) of HSP90 function by targeting HSP90 dimerization via the C-terminal domain (CTD). This was achieved by structure-based molecular design, chemical synthesis, and functional pre-clinical in vitro and in vivo validation using CML cell lines and patient-derived CML cells. Aminoxyrone (AX) is a promising potential candidate, which induces apoptosis in leukemic stem cells (LSCs) fraction (CD34+CD38-) as well as the leukemic bulk (CD34+CD38+) of primary CML and in TKI-resistant cells. Furthermore, BCR-ABL1 oncoprotein and related pro-oncogenic cellular responses are downregulated and targeting HSP90 C-terminus by AX does not induce HSR in vitro and in vivo. We also probed the potential of AX in other therapy refractory leukemia such as BCR-ABL1+ BCP-ALL, FLT3-ITD+ AML and Ph-like BCP-ALL. Therefore, AX is the first peptidometic C-terminal HSP90 inhibitor with the potential to increase TFR in TKI sensitive and refractory CML patients and also offers a novel therapeutic option for patients with other therapy-refractory leukemia, due to its low toxicity profile and lack of HSR