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This article discusses a rare case of inter-nuclear ophthalmoplegia (INO) with upbeat nystagmus and upper motor neuron (UMN) facial paresis in a patient with medial medullary syndrome. The patient, a 55-year-old male with diabetes and hypertension, presented with symptoms of dizziness, vomiting, numbness, and weakness on the left side of the body. Clinical examination revealed adduction restriction of the right eye, left eye abducting nystagmus, upbeat nystagmus, left central facial palsy, and hemiparesis on the left side. Imaging studies confirmed the presence of an acute infarct in the right medial medullary region. The article provides a detailed analysis of the structures involved and discusses the rarity of these symptoms in medial medullary infarctions. [Extracted from the article]

This article discusses a rare case of bilateral medial medullary infarction, a type of stroke that affects less than 0.5% of all cerebral infarcts. The usual presentation of this condition includes contralateral hemiplegia, loss of vibration sensation, and ipsilateral hypoglossal paralysis. However, the patient in this case had an incomplete syndrome, presenting with giddiness, numbness in the right lower limb, and weakness in the right upper and lower limbs. The MRI revealed bilateral ventral medulla infarction with the characteristic "heart appearance sign." The patient was treated with medication and physiotherapy, and her symptoms improved without respiratory failure. [Extracted from the article]

A case study of a 55‑year‑old male, farmer by occupation, who is nonalcoholic and nonsmoker with no comorbidities was admitted to the emergency department with a history of multiple bee stings and presented with swelling and itching over face and neck. Topics include acute infarct in left frontal, parietal, occipital cortical and subcortical regions with no mass effect; and anaphylaxis causing severe hypotension resulting in decreased cerebral hypoperfusion leading to watershed infarct.

Purpose: This comprehensive scoping review of the medical literature on first-generation low-income (FGLI) individuals in medicine aimed to synthesize the highest levels of evidence to inform medical education stakeholders., Method: Database searches were conducted in Academic Search Premier, Education Research Premier, ERIC, Ovid MEDLINE, Ovid Embase, Professional Development Collection, PubMed, Scopus, Google Scholar, and Web of Science Core Collection from database inception through March 15, 2023. English-language articles on first-generation or low-income individuals in medicine from U.S. medical schools were included. Articles were evaluated for level of evidence and themes chosen., Results: Database searches resulted in 27,075 citations, 247 of which qualified for data extraction. The articles were classified by evidence level: level I (n = 2), level II (n = 17), level III (n = 90), level IV (n = 78), and level V (n = 60). Publications reported on 9 major outcomes: exam performance (n = 108), medical school performance (n = 63), residency and fellowship performance (n = 7), honor society status (n = 12), leave of absence (n = 9), withdrawal, dismissal, and attrition (n = 20), medical education graduation (n = 37), career choice (n = 109), and intent to practice in disadvantaged and rural communities (n = 60). Compared with their peers, FGLI individuals had lower medical school and standardized exam scores, enrollment in national medical honor societies and multiple degree programs, and graduate medical education performance and higher rates of leaves of absence, incompletion of medical education, pursuing primary care and family medicine specialties, and intent to practice in underserved communities., Conclusions: Despite an increase in the number of FGLI individuals in medicine, there remains significant opportunity to improve their inclusion and support. Multi-institutional, prospective, risk-adjusted, observational studies are required to determine how to best support FGLI individuals through all medical career stages., (Copyright © 2024 the Association of American Medical Colleges.)

A healthcare-associated group A Streptococcus outbreak involving six patients, four healthcare workers, and one household contact occurred in the labor and delivery unit of an academic medical center. Isolates were highly related by whole genome sequencing. Infection prevention measures, healthcare worker screening, and chemoprophylaxis of those colonized halted further transmission.

Acute motor axonal neuropathy (AMAN) is a variant of Guillain-Barré syndrome (GBS), characterized by acute areflexic flaccid quadriparesis with motor axonal changes and absence of demyelinating findings in electrophysiological studies. A 30-year-old man presented with acute onset flaccid type of weakness involving all four limbs, along with drooping of eyelids. Examination revealed ptosis with restricted horizontal and vertical eye movements. Spinomotor system examination revealed acute flaccid areflexic quadriparesis. Nerve conduction studies (NCS) showed features suggestive of motor axonal neuropathy changes. Cerebrospinal fluid (CSF) revealed albuminocytological dissociation. The diagnosis of AMAN was made, and the patient was treated with intravenous immunoglobulin (IVIg). His weakness gradually improved over 1 month, with partial improvement in ptosis and eye movements. This case highlights the occurrence of ophthalmoparesis in the AMAN variant of GBS. The presence of ophthalmoparesis and areflexia makes it necessary to exclude Miller-Fisher syndrome. But, the presence of axonal changes in nerve conduction study and the profound weakness with negative serum anti-GQ1b antibody profile, supports the diagnosis of AMAN. How to cite this article : Budumuru U, Muralidharan K, Sowmini PR, et al. AMAN with Ophthalmoparesis: A Rare Presentation. J Assoc Physicians India 2023;71(11):103-104., (© Journal of the Association of Physicians of India 2023.)

Study Objectives: To examine the association of self-identified race with sleep quality in heavy smokers., Methods: We studied baseline data from 1965 non-Hispanic White and 462 African American participants from SPIROMICS with ≥ 20 pack-years smoking history. We first examined the Pittsburgh Sleep Quality Index's (PSQI) internal consistency and item-total correlation in a population with chronic obstructive pulmonary disease. We then used staged multivariable regression to investigate the association of race and sleep quality as measured by the PSQI) The first model included demographics, the second added measures of health status, and the third, indicators of socioeconomic status. We next explored the correlation between sleep quality with 6-minute walk distance and St. George's Respiratory Questionnaire score as chronic obstructive pulmonary disease-relevant outcomes. We tested for interactions between self-identified race and the most important determinants of sleep quality in our conceptual model., Results: We found that the PSQI had good internal consistency and item-total correlation in our study population of heavy smokers with and without chronic obstructive pulmonary disease. African American race was associated with increased PSQI in univariable analysis and after adjustment for demographics, health status, and socioenvironmental exposures ( P = .02; 0.44 95%CI: .06 to .83). Increased PSQI was associated with higher postbronchodilator forced expiratory volume in 1 second and lower household income, higher depressive symptoms, and female sex. We identified an interaction wherein depressive symptoms had a greater impact on PSQI score for non-Hispanic White than African American participants ( P for interaction = .01)., Conclusions: In heavy smokers, self-reported African American race is independently associated with worse sleep quality., Clinical Trial Registration: Registry: ClinicalTrials.gov; Name: Study of COPD Subgroups and Biomarkers (SPIROMICS); URL: https://clinicaltrials.gov/ct2/show/NCT01969344; Identifier: NCT01969344., Citation: Baugh AD, Acho M, Arhin A, et al. African American race is associated with worse sleep quality in heavy smokers. J Clin Sleep Med . 2023;19(8):1523-1532., (© 2023 American Academy of Sleep Medicine.)

Background: Antimicrobial resistance (AMR) is rising at an alarming rate and complicating the management of infectious diseases including lower respiratory tract infections (LRTI). Metagenomic next-generation sequencing (mNGS) is a recently established method for culture-independent LRTI diagnosis, but its utility for predicting AMR has remained unclear. We aimed to assess the performance of mNGS for AMR prediction in bacterial LRTI and demonstrate proof of concept for epidemiological AMR surveillance and rapid AMR gene detection using Cas9 enrichment and nanopore sequencing., Methods: We studied 88 patients with acute respiratory failure between 07/2013 and 9/2018, enrolled through a previous observational study of LRTI. Inclusion criteria were age ≥ 18, need for mechanical ventilation, and respiratory specimen collection within 72 h of intubation. Exclusion criteria were decline of study participation, unclear LRTI status, or no matched RNA and DNA mNGS data from a respiratory specimen. Patients with LRTI were identified by clinical adjudication. mNGS was performed on lower respiratory tract specimens. The primary outcome was mNGS performance for predicting phenotypic antimicrobial susceptibility and was assessed in patients with LRTI from culture-confirmed bacterial pathogens with clinical antimicrobial susceptibility testing (n = 27 patients, n = 32 pathogens). Secondary outcomes included the association between hospital exposure and AMR gene burden in the respiratory microbiome (n = 88 patients), and AMR gene detection using Cas9 targeted enrichment and nanopore sequencing (n = 10 patients)., Results: Compared to clinical antimicrobial susceptibility testing, the performance of respiratory mNGS for predicting AMR varied by pathogen, antimicrobial, and nucleic acid type sequenced. For gram-positive bacteria, a combination of RNA + DNA mNGS achieved a sensitivity of 70% (95% confidence interval (CI) 47-87%) and specificity of 95% (CI 85-99%). For gram-negative bacteria, sensitivity was 100% (CI 87-100%) and specificity 64% (CI 48-78%). Patients with hospital-onset LRTI had a greater AMR gene burden in their respiratory microbiome versus those with community-onset LRTI (p = 0.00030), or those without LRTI (p = 0.0024). We found that Cas9 targeted sequencing could enrich for low abundance AMR genes by > 2500-fold and enabled their rapid detection using a nanopore platform., Conclusions: mNGS has utility for the detection and surveillance of resistant bacterial LRTI pathogens., (© 2022. The Author(s).)

Accessibility of multispectral, multitemporal imagery combined with recent advances in cloud computing and machine learning approaches have enhanced our ability to model habitat characteristics across broad spatial and temporal scales. We integrated a large dataset of known nest and roost sites of a threatened species, the Mexican spotted owl (Strix occidentalis lucida), in the southwestern USA with Landsat imagery processed using the Continuous Change Detection and Classification (CCDC) time series algorithm on Google Earth Engine. We then used maximum entropy modeling (Maxent) to classify the landscape into four 'spectral similarity' classes that reflected the degree to which 30-m pixels contained a multispectral signature similar to that found at known owl nest/roost sites and mapped spectral similarity classes from 1986-2020. For map interpretation, we used nationally consistent forest inventory data to evaluate the structural and compositional characteristics of each spectral similarity class. We found a monotonic increase of structural characteristics typically associated with owl nesting and roosting over classes of increasing similarity, with the 'very similar' class meeting or exceeding published minimum desired management conditions for owl nesting and roosting. We also found an increased rate of loss of forest vegetation typical of owl nesting and roosting since the beginning of the 21st century that can be partly attributed to increased frequency and extent of large (≥400 ha) wildfires. This loss resulted in a 38% reduction over the 35-year study period in forest vegetation most similar to that used for owl nesting and roosting. Our modelling approach using cloud computing with time series of Landsat imagery provided a cost-effective tool for landscape-scale, multidecadal monitoring of vegetative components of a threatened species' habitat. Our approach could be used to monitor trends in the vegetation favored by any other species, provided that high-quality location data such as we presented here are available., Competing Interests: The authors have declared that no competing interests exist.